Homework2_ANS500AB_Andrea

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Andrea

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library(tidyverse)
Warning: package 'tidyverse' was built under R version 4.1.3
Warning: package 'ggplot2' was built under R version 4.1.3
Warning: package 'tibble' was built under R version 4.1.3
Warning: package 'tidyr' was built under R version 4.1.3
Warning: package 'readr' was built under R version 4.1.3
Warning: package 'purrr' was built under R version 4.1.3
Warning: package 'dplyr' was built under R version 4.1.3
Warning: package 'stringr' was built under R version 4.1.3
Warning: package 'forcats' was built under R version 4.1.3
Warning: package 'lubridate' was built under R version 4.1.3
-- Attaching core tidyverse packages ------------------------ tidyverse 2.0.0 --
v dplyr     1.1.2     v readr     2.1.4
v forcats   1.0.0     v stringr   1.5.0
v ggplot2   3.4.2     v tibble    3.2.1
v lubridate 1.9.2     v tidyr     1.3.0
v purrr     1.0.1     
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
i Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(car)
Warning: package 'car' was built under R version 4.1.3
Loading required package: carData

Attaching package: 'car'

The following object is masked from 'package:dplyr':

    recode

The following object is masked from 'package:purrr':

    some
data1 <- read.csv("Milk_Production.csv", colClasses = c(NA, "numeric"))
head(data1)
  EweType Diet Week MilkProd
1       2    1    0     1260
2       2    1    0     1900
3       2    1    0     1380
4       2    1    0     3910
5       2    1    0     2900
6       2    2    0     2210
str(data1)
'data.frame':   240 obs. of  4 variables:
 $ EweType : int  2 2 2 2 2 2 2 2 2 2 ...
 $ Diet    : num  1 1 1 1 1 2 2 2 2 2 ...
 $ Week    : int  0 0 0 0 0 0 0 0 0 0 ...
 $ MilkProd: num  1260 1900 1380 3910 2900 2210 1850 1750 1900 1950 ...
glimpse(data1)
Rows: 240
Columns: 4
$ EweType  <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1~
$ Diet     <dbl> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 2~
$ Week     <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0~
$ MilkProd <dbl> 1260, 1900, 1380, 3910, 2900, 2210, 1850, 1750, 1900, 1950, 1~
data1$EweType<- as.factor(data1$EweType)
data1$Diet<- as.factor(data1$Diet)
data1$Week <- as.integer(data1$Week)
data1$MilkProd<- as.numeric(data1$MilkProd)
tail(data1)
    EweType Diet Week MilkProd
235       1    2    7     1000
236       1    3    7      550
237       1    3    7      820
238       1    3    7      520
239       1    3    7      630
240       1    3    7      500
###Question 1####
##part a ###
data1 %>%
  arrange(Week)
    EweType Diet Week MilkProd
1         2    1    0     1260
2         2    1    0     1900
3         2    1    0     1380
4         2    1    0     3910
5         2    1    0     2900
6         2    2    0     2210
7         2    2    0     1850
8         2    2    0     1750
9         2    2    0     1900
10        2    2    0     1950
11        2    3    0     1190
12        2    3    0     1190
13        2    3    0      590
14        2    3    0     1410
15        2    3    0     1320
16        1    1    0     4120
17        1    1    0     3530
18        1    1    0     1940
19        1    1    0     3130
20        1    1    0     3230
21        1    2    0     1480
22        1    2    0     2180
23        1    2    0     2610
24        1    2    0     2320
25        1    2    0     1740
26        1    3    0     1740
27        1    3    0     1680
28        1    3    0     1890
29        1    3    0     1970
30        1    3    0     2770
31        2    1    1     1640
32        2    1    1     2570
33        2    1    1     2760
34        2    1    1     3190
35        2    1    1     2440
36        2    2    1     2330
37        2    2    1      930
38        2    2    1     1810
39        2    2    1     1500
40        2    2    1     1800
41        2    3    1      760
42        2    3    1     1030
43        2    3    1      910
44        2    3    1      990
45        2    3    1      950
46        1    1    1     4810
47        1    1    1     3040
48        1    1    1     2000
49        1    1    1     2440
50        1    1    1     4040
51        1    2    1     1870
52        1    2    1     1700
53        1    2    1     1850
54        1    2    1     1420
55        1    2    1     1260
56        1    3    1     1190
57        1    3    1     1240
58        1    3    1     1380
59        1    3    1     1170
60        1    3    1     1790
61        2    1    2     1080
62        2    1    2     1100
63        2    1    2     1550
64        2    1    2     1050
65        2    1    2     1280
66        2    2    2     1700
67        2    2    2      850
68        2    2    2     1540
69        2    2    2      950
70        2    2    2     1350
71        2    3    2      540
72        2    3    2      700
73        2    3    2      600
74        2    3    2      750
75        2    3    2      700
76        1    1    2     1850
77        1    1    2     1380
78        1    1    2     1650
79        1    1    2     1230
80        1    1    2     1580
81        1    2    2     1500
82        1    2    2     1380
83        1    2    2     1120
84        1    2    2     1130
85        1    2    2      860
86        1    3    2      960
87        1    3    2     1080
88        1    3    2     1120
89        1    3    2      960
90        1    3    2     1020
91        2    1    3     1000
92        2    1    3     1520
93        2    1    3      980
94        2    1    3     1180
95        2    1    3     1540
96        2    2    3     1180
97        2    2    3      780
98        2    2    3     1210
99        2    2    3      500
100       2    2    3     1000
101       2    3    3      500
102       2    3    3      500
103       2    3    3      320
104       2    3    3      240
105       2    3    3      460
106       1    1    3     1600
107       1    1    3     1250
108       1    1    3     1420
109       1    1    3     1020
110       1    1    3     1450
111       1    2    3     1300
112       1    2    3     1100
113       1    2    3      750
114       1    2    3      900
115       1    2    3      640
116       1    3    3      600
117       1    3    3      980
118       1    3    3      940
119       1    3    3      750
120       1    3    3      570
121       2    1    4      950
122       2    1    4     1200
123       2    1    4     1380
124       2    1    4      980
125       2    1    4      740
126       2    2    4      890
127       2    2    4      380
128       2    2    4      810
129       2    2    4      260
130       2    2    4      800
131       2    3    4      370
132       2    3    4      350
133       2    3    4      250
134       2    3    4      170
135       2    3    4      380
136       1    1    4     1680
137       1    1    4     1200
138       1    1    4      960
139       1    1    4     1100
140       1    1    4      620
141       1    2    4      900
142       1    2    4      720
143       1    2    4      680
144       1    2    4      480
145       1    2    4      800
146       1    3    4      700
147       1    3    4      800
148       1    3    4      680
149       1    3    4      400
150       1    3    4      420
151       2    1    5     1000
152       2    1    5     1300
153       2    1    5     1000
154       2    1    5      850
155       2    1    5      800
156       2    2    5      850
157       2    2    5      300
158       2    2    5      600
159       2    2    5      300
160       2    2    5      650
161       2    3    5      250
162       2    3    5      250
163       2    3    5      200
164       2    3    5      100
165       2    3    5      270
166       1    1    5     1380
167       1    1    5      920
168       1    1    5     1280
169       1    1    5     1120
170       1    1    5      800
171       1    2    5      640
172       1    2    5      800
173       1    2    5      420
174       1    2    5      380
175       1    2    5      900
176       1    3    5      660
177       1    3    5      760
178       1    3    5      640
179       1    3    5      480
180       1    3    5      460
181       2    1    6      900
182       2    1    6     1350
183       2    1    6     1300
184       2    1    6     1100
185       2    1    6      600
186       2    2    6      750
187       2    2    6      560
188       2    2    6      750
189       2    2    6      250
190       2    2    6      600
191       2    3    6      360
192       2    3    6      300
193       2    3    6      150
194       2    3    6      200
195       2    3    6      200
196       1    1    6     1100
197       1    1    6      850
198       1    1    6     1100
199       1    1    6     1200
200       1    1    6      750
201       1    2    6      400
202       1    2    6      520
203       1    2    6      500
204       1    2    6      400
205       1    2    6      950
206       1    3    6      650
207       1    3    6      900
208       1    3    6      850
209       1    3    6      500
210       1    3    6      400
211       2    1    7      800
212       2    1    7     1250
213       2    1    7     1050
214       2    1    7      950
215       2    1    7      500
216       2    2    7      600
217       2    2    7      350
218       2    2    7      500
219       2    2    7      200
220       2    2    7      500
221       2    3    7      300
222       2    3    7      100
223       2    3    7      100
224       2    3    7      200
225       2    3    7      100
226       1    1    7     1000
227       1    1    7     1150
228       1    1    7     1120
229       1    1    7     1450
230       1    1    7      660
231       1    2    7      780
232       1    2    7      620
233       1    2    7      550
234       1    2    7      450
235       1    2    7     1000
236       1    3    7      550
237       1    3    7      820
238       1    3    7      520
239       1    3    7      630
240       1    3    7      500
data1%>%
  arrange(EweType)
    EweType Diet Week MilkProd
1         1    1    0     4120
2         1    1    0     3530
3         1    1    0     1940
4         1    1    0     3130
5         1    1    0     3230
6         1    2    0     1480
7         1    2    0     2180
8         1    2    0     2610
9         1    2    0     2320
10        1    2    0     1740
11        1    3    0     1740
12        1    3    0     1680
13        1    3    0     1890
14        1    3    0     1970
15        1    3    0     2770
16        1    1    1     4810
17        1    1    1     3040
18        1    1    1     2000
19        1    1    1     2440
20        1    1    1     4040
21        1    2    1     1870
22        1    2    1     1700
23        1    2    1     1850
24        1    2    1     1420
25        1    2    1     1260
26        1    3    1     1190
27        1    3    1     1240
28        1    3    1     1380
29        1    3    1     1170
30        1    3    1     1790
31        1    1    2     1850
32        1    1    2     1380
33        1    1    2     1650
34        1    1    2     1230
35        1    1    2     1580
36        1    2    2     1500
37        1    2    2     1380
38        1    2    2     1120
39        1    2    2     1130
40        1    2    2      860
41        1    3    2      960
42        1    3    2     1080
43        1    3    2     1120
44        1    3    2      960
45        1    3    2     1020
46        1    1    3     1600
47        1    1    3     1250
48        1    1    3     1420
49        1    1    3     1020
50        1    1    3     1450
51        1    2    3     1300
52        1    2    3     1100
53        1    2    3      750
54        1    2    3      900
55        1    2    3      640
56        1    3    3      600
57        1    3    3      980
58        1    3    3      940
59        1    3    3      750
60        1    3    3      570
61        1    1    4     1680
62        1    1    4     1200
63        1    1    4      960
64        1    1    4     1100
65        1    1    4      620
66        1    2    4      900
67        1    2    4      720
68        1    2    4      680
69        1    2    4      480
70        1    2    4      800
71        1    3    4      700
72        1    3    4      800
73        1    3    4      680
74        1    3    4      400
75        1    3    4      420
76        1    1    5     1380
77        1    1    5      920
78        1    1    5     1280
79        1    1    5     1120
80        1    1    5      800
81        1    2    5      640
82        1    2    5      800
83        1    2    5      420
84        1    2    5      380
85        1    2    5      900
86        1    3    5      660
87        1    3    5      760
88        1    3    5      640
89        1    3    5      480
90        1    3    5      460
91        1    1    6     1100
92        1    1    6      850
93        1    1    6     1100
94        1    1    6     1200
95        1    1    6      750
96        1    2    6      400
97        1    2    6      520
98        1    2    6      500
99        1    2    6      400
100       1    2    6      950
101       1    3    6      650
102       1    3    6      900
103       1    3    6      850
104       1    3    6      500
105       1    3    6      400
106       1    1    7     1000
107       1    1    7     1150
108       1    1    7     1120
109       1    1    7     1450
110       1    1    7      660
111       1    2    7      780
112       1    2    7      620
113       1    2    7      550
114       1    2    7      450
115       1    2    7     1000
116       1    3    7      550
117       1    3    7      820
118       1    3    7      520
119       1    3    7      630
120       1    3    7      500
121       2    1    0     1260
122       2    1    0     1900
123       2    1    0     1380
124       2    1    0     3910
125       2    1    0     2900
126       2    2    0     2210
127       2    2    0     1850
128       2    2    0     1750
129       2    2    0     1900
130       2    2    0     1950
131       2    3    0     1190
132       2    3    0     1190
133       2    3    0      590
134       2    3    0     1410
135       2    3    0     1320
136       2    1    1     1640
137       2    1    1     2570
138       2    1    1     2760
139       2    1    1     3190
140       2    1    1     2440
141       2    2    1     2330
142       2    2    1      930
143       2    2    1     1810
144       2    2    1     1500
145       2    2    1     1800
146       2    3    1      760
147       2    3    1     1030
148       2    3    1      910
149       2    3    1      990
150       2    3    1      950
151       2    1    2     1080
152       2    1    2     1100
153       2    1    2     1550
154       2    1    2     1050
155       2    1    2     1280
156       2    2    2     1700
157       2    2    2      850
158       2    2    2     1540
159       2    2    2      950
160       2    2    2     1350
161       2    3    2      540
162       2    3    2      700
163       2    3    2      600
164       2    3    2      750
165       2    3    2      700
166       2    1    3     1000
167       2    1    3     1520
168       2    1    3      980
169       2    1    3     1180
170       2    1    3     1540
171       2    2    3     1180
172       2    2    3      780
173       2    2    3     1210
174       2    2    3      500
175       2    2    3     1000
176       2    3    3      500
177       2    3    3      500
178       2    3    3      320
179       2    3    3      240
180       2    3    3      460
181       2    1    4      950
182       2    1    4     1200
183       2    1    4     1380
184       2    1    4      980
185       2    1    4      740
186       2    2    4      890
187       2    2    4      380
188       2    2    4      810
189       2    2    4      260
190       2    2    4      800
191       2    3    4      370
192       2    3    4      350
193       2    3    4      250
194       2    3    4      170
195       2    3    4      380
196       2    1    5     1000
197       2    1    5     1300
198       2    1    5     1000
199       2    1    5      850
200       2    1    5      800
201       2    2    5      850
202       2    2    5      300
203       2    2    5      600
204       2    2    5      300
205       2    2    5      650
206       2    3    5      250
207       2    3    5      250
208       2    3    5      200
209       2    3    5      100
210       2    3    5      270
211       2    1    6      900
212       2    1    6     1350
213       2    1    6     1300
214       2    1    6     1100
215       2    1    6      600
216       2    2    6      750
217       2    2    6      560
218       2    2    6      750
219       2    2    6      250
220       2    2    6      600
221       2    3    6      360
222       2    3    6      300
223       2    3    6      150
224       2    3    6      200
225       2    3    6      200
226       2    1    7      800
227       2    1    7     1250
228       2    1    7     1050
229       2    1    7      950
230       2    1    7      500
231       2    2    7      600
232       2    2    7      350
233       2    2    7      500
234       2    2    7      200
235       2    2    7      500
236       2    3    7      300
237       2    3    7      100
238       2    3    7      100
239       2    3    7      200
240       2    3    7      100
##part b ###
data1 %>%
  arrange(desc(Week))
    EweType Diet Week MilkProd
1         2    1    7      800
2         2    1    7     1250
3         2    1    7     1050
4         2    1    7      950
5         2    1    7      500
6         2    2    7      600
7         2    2    7      350
8         2    2    7      500
9         2    2    7      200
10        2    2    7      500
11        2    3    7      300
12        2    3    7      100
13        2    3    7      100
14        2    3    7      200
15        2    3    7      100
16        1    1    7     1000
17        1    1    7     1150
18        1    1    7     1120
19        1    1    7     1450
20        1    1    7      660
21        1    2    7      780
22        1    2    7      620
23        1    2    7      550
24        1    2    7      450
25        1    2    7     1000
26        1    3    7      550
27        1    3    7      820
28        1    3    7      520
29        1    3    7      630
30        1    3    7      500
31        2    1    6      900
32        2    1    6     1350
33        2    1    6     1300
34        2    1    6     1100
35        2    1    6      600
36        2    2    6      750
37        2    2    6      560
38        2    2    6      750
39        2    2    6      250
40        2    2    6      600
41        2    3    6      360
42        2    3    6      300
43        2    3    6      150
44        2    3    6      200
45        2    3    6      200
46        1    1    6     1100
47        1    1    6      850
48        1    1    6     1100
49        1    1    6     1200
50        1    1    6      750
51        1    2    6      400
52        1    2    6      520
53        1    2    6      500
54        1    2    6      400
55        1    2    6      950
56        1    3    6      650
57        1    3    6      900
58        1    3    6      850
59        1    3    6      500
60        1    3    6      400
61        2    1    5     1000
62        2    1    5     1300
63        2    1    5     1000
64        2    1    5      850
65        2    1    5      800
66        2    2    5      850
67        2    2    5      300
68        2    2    5      600
69        2    2    5      300
70        2    2    5      650
71        2    3    5      250
72        2    3    5      250
73        2    3    5      200
74        2    3    5      100
75        2    3    5      270
76        1    1    5     1380
77        1    1    5      920
78        1    1    5     1280
79        1    1    5     1120
80        1    1    5      800
81        1    2    5      640
82        1    2    5      800
83        1    2    5      420
84        1    2    5      380
85        1    2    5      900
86        1    3    5      660
87        1    3    5      760
88        1    3    5      640
89        1    3    5      480
90        1    3    5      460
91        2    1    4      950
92        2    1    4     1200
93        2    1    4     1380
94        2    1    4      980
95        2    1    4      740
96        2    2    4      890
97        2    2    4      380
98        2    2    4      810
99        2    2    4      260
100       2    2    4      800
101       2    3    4      370
102       2    3    4      350
103       2    3    4      250
104       2    3    4      170
105       2    3    4      380
106       1    1    4     1680
107       1    1    4     1200
108       1    1    4      960
109       1    1    4     1100
110       1    1    4      620
111       1    2    4      900
112       1    2    4      720
113       1    2    4      680
114       1    2    4      480
115       1    2    4      800
116       1    3    4      700
117       1    3    4      800
118       1    3    4      680
119       1    3    4      400
120       1    3    4      420
121       2    1    3     1000
122       2    1    3     1520
123       2    1    3      980
124       2    1    3     1180
125       2    1    3     1540
126       2    2    3     1180
127       2    2    3      780
128       2    2    3     1210
129       2    2    3      500
130       2    2    3     1000
131       2    3    3      500
132       2    3    3      500
133       2    3    3      320
134       2    3    3      240
135       2    3    3      460
136       1    1    3     1600
137       1    1    3     1250
138       1    1    3     1420
139       1    1    3     1020
140       1    1    3     1450
141       1    2    3     1300
142       1    2    3     1100
143       1    2    3      750
144       1    2    3      900
145       1    2    3      640
146       1    3    3      600
147       1    3    3      980
148       1    3    3      940
149       1    3    3      750
150       1    3    3      570
151       2    1    2     1080
152       2    1    2     1100
153       2    1    2     1550
154       2    1    2     1050
155       2    1    2     1280
156       2    2    2     1700
157       2    2    2      850
158       2    2    2     1540
159       2    2    2      950
160       2    2    2     1350
161       2    3    2      540
162       2    3    2      700
163       2    3    2      600
164       2    3    2      750
165       2    3    2      700
166       1    1    2     1850
167       1    1    2     1380
168       1    1    2     1650
169       1    1    2     1230
170       1    1    2     1580
171       1    2    2     1500
172       1    2    2     1380
173       1    2    2     1120
174       1    2    2     1130
175       1    2    2      860
176       1    3    2      960
177       1    3    2     1080
178       1    3    2     1120
179       1    3    2      960
180       1    3    2     1020
181       2    1    1     1640
182       2    1    1     2570
183       2    1    1     2760
184       2    1    1     3190
185       2    1    1     2440
186       2    2    1     2330
187       2    2    1      930
188       2    2    1     1810
189       2    2    1     1500
190       2    2    1     1800
191       2    3    1      760
192       2    3    1     1030
193       2    3    1      910
194       2    3    1      990
195       2    3    1      950
196       1    1    1     4810
197       1    1    1     3040
198       1    1    1     2000
199       1    1    1     2440
200       1    1    1     4040
201       1    2    1     1870
202       1    2    1     1700
203       1    2    1     1850
204       1    2    1     1420
205       1    2    1     1260
206       1    3    1     1190
207       1    3    1     1240
208       1    3    1     1380
209       1    3    1     1170
210       1    3    1     1790
211       2    1    0     1260
212       2    1    0     1900
213       2    1    0     1380
214       2    1    0     3910
215       2    1    0     2900
216       2    2    0     2210
217       2    2    0     1850
218       2    2    0     1750
219       2    2    0     1900
220       2    2    0     1950
221       2    3    0     1190
222       2    3    0     1190
223       2    3    0      590
224       2    3    0     1410
225       2    3    0     1320
226       1    1    0     4120
227       1    1    0     3530
228       1    1    0     1940
229       1    1    0     3130
230       1    1    0     3230
231       1    2    0     1480
232       1    2    0     2180
233       1    2    0     2610
234       1    2    0     2320
235       1    2    0     1740
236       1    3    0     1740
237       1    3    0     1680
238       1    3    0     1890
239       1    3    0     1970
240       1    3    0     2770
data1 %>%
  arrange(desc(MilkProd))
    EweType Diet Week MilkProd
1         1    1    1     4810
2         1    1    0     4120
3         1    1    1     4040
4         2    1    0     3910
5         1    1    0     3530
6         1    1    0     3230
7         2    1    1     3190
8         1    1    0     3130
9         1    1    1     3040
10        2    1    0     2900
11        1    3    0     2770
12        2    1    1     2760
13        1    2    0     2610
14        2    1    1     2570
15        2    1    1     2440
16        1    1    1     2440
17        2    2    1     2330
18        1    2    0     2320
19        2    2    0     2210
20        1    2    0     2180
21        1    1    1     2000
22        1    3    0     1970
23        2    2    0     1950
24        1    1    0     1940
25        2    1    0     1900
26        2    2    0     1900
27        1    3    0     1890
28        1    2    1     1870
29        2    2    0     1850
30        1    2    1     1850
31        1    1    2     1850
32        2    2    1     1810
33        2    2    1     1800
34        1    3    1     1790
35        2    2    0     1750
36        1    2    0     1740
37        1    3    0     1740
38        1    2    1     1700
39        2    2    2     1700
40        1    3    0     1680
41        1    1    4     1680
42        1    1    2     1650
43        2    1    1     1640
44        1    1    3     1600
45        1    1    2     1580
46        2    1    2     1550
47        2    2    2     1540
48        2    1    3     1540
49        2    1    3     1520
50        2    2    1     1500
51        1    2    2     1500
52        1    2    0     1480
53        1    1    3     1450
54        1    1    7     1450
55        1    2    1     1420
56        1    1    3     1420
57        2    3    0     1410
58        2    1    0     1380
59        1    3    1     1380
60        1    1    2     1380
61        1    2    2     1380
62        2    1    4     1380
63        1    1    5     1380
64        2    2    2     1350
65        2    1    6     1350
66        2    3    0     1320
67        1    2    3     1300
68        2    1    5     1300
69        2    1    6     1300
70        2    1    2     1280
71        1    1    5     1280
72        2    1    0     1260
73        1    2    1     1260
74        1    1    3     1250
75        2    1    7     1250
76        1    3    1     1240
77        1    1    2     1230
78        2    2    3     1210
79        2    1    4     1200
80        1    1    4     1200
81        1    1    6     1200
82        2    3    0     1190
83        2    3    0     1190
84        1    3    1     1190
85        2    1    3     1180
86        2    2    3     1180
87        1    3    1     1170
88        1    1    7     1150
89        1    2    2     1130
90        1    2    2     1120
91        1    3    2     1120
92        1    1    5     1120
93        1    1    7     1120
94        2    1    2     1100
95        1    2    3     1100
96        1    1    4     1100
97        2    1    6     1100
98        1    1    6     1100
99        1    1    6     1100
100       2    1    2     1080
101       1    3    2     1080
102       2    1    2     1050
103       2    1    7     1050
104       2    3    1     1030
105       1    3    2     1020
106       1    1    3     1020
107       2    1    3     1000
108       2    2    3     1000
109       2    1    5     1000
110       2    1    5     1000
111       1    1    7     1000
112       1    2    7     1000
113       2    3    1      990
114       2    1    3      980
115       1    3    3      980
116       2    1    4      980
117       1    3    2      960
118       1    3    2      960
119       1    1    4      960
120       2    3    1      950
121       2    2    2      950
122       2    1    4      950
123       1    2    6      950
124       2    1    7      950
125       1    3    3      940
126       2    2    1      930
127       1    1    5      920
128       2    3    1      910
129       1    2    3      900
130       1    2    4      900
131       1    2    5      900
132       2    1    6      900
133       1    3    6      900
134       2    2    4      890
135       1    2    2      860
136       2    2    2      850
137       2    1    5      850
138       2    2    5      850
139       1    1    6      850
140       1    3    6      850
141       1    3    7      820
142       2    2    4      810
143       2    2    4      800
144       1    2    4      800
145       1    3    4      800
146       2    1    5      800
147       1    1    5      800
148       1    2    5      800
149       2    1    7      800
150       2    2    3      780
151       1    2    7      780
152       2    3    1      760
153       1    3    5      760
154       2    3    2      750
155       1    2    3      750
156       1    3    3      750
157       2    2    6      750
158       2    2    6      750
159       1    1    6      750
160       2    1    4      740
161       1    2    4      720
162       2    3    2      700
163       2    3    2      700
164       1    3    4      700
165       1    2    4      680
166       1    3    4      680
167       1    3    5      660
168       1    1    7      660
169       2    2    5      650
170       1    3    6      650
171       1    2    3      640
172       1    2    5      640
173       1    3    5      640
174       1    3    7      630
175       1    1    4      620
176       1    2    7      620
177       2    3    2      600
178       1    3    3      600
179       2    2    5      600
180       2    1    6      600
181       2    2    6      600
182       2    2    7      600
183       2    3    0      590
184       1    3    3      570
185       2    2    6      560
186       1    2    7      550
187       1    3    7      550
188       2    3    2      540
189       1    2    6      520
190       1    3    7      520
191       2    2    3      500
192       2    3    3      500
193       2    3    3      500
194       1    2    6      500
195       1    3    6      500
196       2    1    7      500
197       2    2    7      500
198       2    2    7      500
199       1    3    7      500
200       1    2    4      480
201       1    3    5      480
202       2    3    3      460
203       1    3    5      460
204       1    2    7      450
205       1    3    4      420
206       1    2    5      420
207       1    3    4      400
208       1    2    6      400
209       1    2    6      400
210       1    3    6      400
211       2    2    4      380
212       2    3    4      380
213       1    2    5      380
214       2    3    4      370
215       2    3    6      360
216       2    3    4      350
217       2    2    7      350
218       2    3    3      320
219       2    2    5      300
220       2    2    5      300
221       2    3    6      300
222       2    3    7      300
223       2    3    5      270
224       2    2    4      260
225       2    3    4      250
226       2    3    5      250
227       2    3    5      250
228       2    2    6      250
229       2    3    3      240
230       2    3    5      200
231       2    3    6      200
232       2    3    6      200
233       2    2    7      200
234       2    3    7      200
235       2    3    4      170
236       2    3    6      150
237       2    3    5      100
238       2    3    7      100
239       2    3    7      100
240       2    3    7      100
##part c ###
data1 %>%
  filter(Week =="7")
   EweType Diet Week MilkProd
1        2    1    7      800
2        2    1    7     1250
3        2    1    7     1050
4        2    1    7      950
5        2    1    7      500
6        2    2    7      600
7        2    2    7      350
8        2    2    7      500
9        2    2    7      200
10       2    2    7      500
11       2    3    7      300
12       2    3    7      100
13       2    3    7      100
14       2    3    7      200
15       2    3    7      100
16       1    1    7     1000
17       1    1    7     1150
18       1    1    7     1120
19       1    1    7     1450
20       1    1    7      660
21       1    2    7      780
22       1    2    7      620
23       1    2    7      550
24       1    2    7      450
25       1    2    7     1000
26       1    3    7      550
27       1    3    7      820
28       1    3    7      520
29       1    3    7      630
30       1    3    7      500
##part d ###
data1$MilkProd > 2000
  [1] FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
 [13] FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE
 [25] FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
 [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE
 [49]  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[157] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[169] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[181] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[193] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[205] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[217] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[229] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
##part e ###
data1 %>%
  filter(Week != 0)
    EweType Diet Week MilkProd
1         2    1    1     1640
2         2    1    1     2570
3         2    1    1     2760
4         2    1    1     3190
5         2    1    1     2440
6         2    2    1     2330
7         2    2    1      930
8         2    2    1     1810
9         2    2    1     1500
10        2    2    1     1800
11        2    3    1      760
12        2    3    1     1030
13        2    3    1      910
14        2    3    1      990
15        2    3    1      950
16        1    1    1     4810
17        1    1    1     3040
18        1    1    1     2000
19        1    1    1     2440
20        1    1    1     4040
21        1    2    1     1870
22        1    2    1     1700
23        1    2    1     1850
24        1    2    1     1420
25        1    2    1     1260
26        1    3    1     1190
27        1    3    1     1240
28        1    3    1     1380
29        1    3    1     1170
30        1    3    1     1790
31        2    1    2     1080
32        2    1    2     1100
33        2    1    2     1550
34        2    1    2     1050
35        2    1    2     1280
36        2    2    2     1700
37        2    2    2      850
38        2    2    2     1540
39        2    2    2      950
40        2    2    2     1350
41        2    3    2      540
42        2    3    2      700
43        2    3    2      600
44        2    3    2      750
45        2    3    2      700
46        1    1    2     1850
47        1    1    2     1380
48        1    1    2     1650
49        1    1    2     1230
50        1    1    2     1580
51        1    2    2     1500
52        1    2    2     1380
53        1    2    2     1120
54        1    2    2     1130
55        1    2    2      860
56        1    3    2      960
57        1    3    2     1080
58        1    3    2     1120
59        1    3    2      960
60        1    3    2     1020
61        2    1    3     1000
62        2    1    3     1520
63        2    1    3      980
64        2    1    3     1180
65        2    1    3     1540
66        2    2    3     1180
67        2    2    3      780
68        2    2    3     1210
69        2    2    3      500
70        2    2    3     1000
71        2    3    3      500
72        2    3    3      500
73        2    3    3      320
74        2    3    3      240
75        2    3    3      460
76        1    1    3     1600
77        1    1    3     1250
78        1    1    3     1420
79        1    1    3     1020
80        1    1    3     1450
81        1    2    3     1300
82        1    2    3     1100
83        1    2    3      750
84        1    2    3      900
85        1    2    3      640
86        1    3    3      600
87        1    3    3      980
88        1    3    3      940
89        1    3    3      750
90        1    3    3      570
91        2    1    4      950
92        2    1    4     1200
93        2    1    4     1380
94        2    1    4      980
95        2    1    4      740
96        2    2    4      890
97        2    2    4      380
98        2    2    4      810
99        2    2    4      260
100       2    2    4      800
101       2    3    4      370
102       2    3    4      350
103       2    3    4      250
104       2    3    4      170
105       2    3    4      380
106       1    1    4     1680
107       1    1    4     1200
108       1    1    4      960
109       1    1    4     1100
110       1    1    4      620
111       1    2    4      900
112       1    2    4      720
113       1    2    4      680
114       1    2    4      480
115       1    2    4      800
116       1    3    4      700
117       1    3    4      800
118       1    3    4      680
119       1    3    4      400
120       1    3    4      420
121       2    1    5     1000
122       2    1    5     1300
123       2    1    5     1000
124       2    1    5      850
125       2    1    5      800
126       2    2    5      850
127       2    2    5      300
128       2    2    5      600
129       2    2    5      300
130       2    2    5      650
131       2    3    5      250
132       2    3    5      250
133       2    3    5      200
134       2    3    5      100
135       2    3    5      270
136       1    1    5     1380
137       1    1    5      920
138       1    1    5     1280
139       1    1    5     1120
140       1    1    5      800
141       1    2    5      640
142       1    2    5      800
143       1    2    5      420
144       1    2    5      380
145       1    2    5      900
146       1    3    5      660
147       1    3    5      760
148       1    3    5      640
149       1    3    5      480
150       1    3    5      460
151       2    1    6      900
152       2    1    6     1350
153       2    1    6     1300
154       2    1    6     1100
155       2    1    6      600
156       2    2    6      750
157       2    2    6      560
158       2    2    6      750
159       2    2    6      250
160       2    2    6      600
161       2    3    6      360
162       2    3    6      300
163       2    3    6      150
164       2    3    6      200
165       2    3    6      200
166       1    1    6     1100
167       1    1    6      850
168       1    1    6     1100
169       1    1    6     1200
170       1    1    6      750
171       1    2    6      400
172       1    2    6      520
173       1    2    6      500
174       1    2    6      400
175       1    2    6      950
176       1    3    6      650
177       1    3    6      900
178       1    3    6      850
179       1    3    6      500
180       1    3    6      400
181       2    1    7      800
182       2    1    7     1250
183       2    1    7     1050
184       2    1    7      950
185       2    1    7      500
186       2    2    7      600
187       2    2    7      350
188       2    2    7      500
189       2    2    7      200
190       2    2    7      500
191       2    3    7      300
192       2    3    7      100
193       2    3    7      100
194       2    3    7      200
195       2    3    7      100
196       1    1    7     1000
197       1    1    7     1150
198       1    1    7     1120
199       1    1    7     1450
200       1    1    7      660
201       1    2    7      780
202       1    2    7      620
203       1    2    7      550
204       1    2    7      450
205       1    2    7     1000
206       1    3    7      550
207       1    3    7      820
208       1    3    7      520
209       1    3    7      630
210       1    3    7      500
##part f ###
data1 %>%
  filter(EweType == "1", Week == "0")
   EweType Diet Week MilkProd
1        1    1    0     4120
2        1    1    0     3530
3        1    1    0     1940
4        1    1    0     3130
5        1    1    0     3230
6        1    2    0     1480
7        1    2    0     2180
8        1    2    0     2610
9        1    2    0     2320
10       1    2    0     1740
11       1    3    0     1740
12       1    3    0     1680
13       1    3    0     1890
14       1    3    0     1970
15       1    3    0     2770
data1 %>%
  filter(EweType == "1", Week == "1")
   EweType Diet Week MilkProd
1        1    1    1     4810
2        1    1    1     3040
3        1    1    1     2000
4        1    1    1     2440
5        1    1    1     4040
6        1    2    1     1870
7        1    2    1     1700
8        1    2    1     1850
9        1    2    1     1420
10       1    2    1     1260
11       1    3    1     1190
12       1    3    1     1240
13       1    3    1     1380
14       1    3    1     1170
15       1    3    1     1790
##part g ###
data1 %>%
  slice_head(n=5)
  EweType Diet Week MilkProd
1       2    1    0     1260
2       2    1    0     1900
3       2    1    0     1380
4       2    1    0     3910
5       2    1    0     2900
##part h ###
data1%>%
  slice_sample(prop = 0.20)
   EweType Diet Week MilkProd
1        1    2    1     1420
2        1    1    3     1450
3        1    3    0     2770
4        1    3    6      650
5        1    1    6     1200
6        1    1    1     4040
7        1    2    4      480
8        2    1    3     1520
9        2    3    6      150
10       1    3    5      460
11       2    2    5      650
12       1    2    6      400
13       2    3    3      460
14       1    1    0     1940
15       1    3    0     1890
16       2    3    4      350
17       1    3    5      660
18       2    1    0     1380
19       2    3    5      200
20       1    2    3      900
21       2    2    7      500
22       2    3    7      100
23       2    1    6     1100
24       2    1    1     2760
25       2    1    5      850
26       1    1    2     1580
27       2    3    2      600
28       1    3    2     1080
29       2    1    7      500
30       2    2    3     1210
31       1    1    5      920
32       1    3    4      680
33       1    3    2      960
34       2    3    5      250
35       1    1    5     1380
36       1    1    1     2440
37       2    1    1     2440
38       1    2    3      640
39       2    3    5      100
40       2    2    7      500
41       1    3    7      820
42       1    3    3      980
43       1    3    4      400
44       2    3    4      170
45       2    1    3      980
46       2    1    6     1300
47       2    1    3     1180
48       2    2    4      800
##part i ###
data1 %>%
  slice_min(MilkProd, n=5)
  EweType Diet Week MilkProd
1       2    3    5      100
2       2    3    7      100
3       2    3    7      100
4       2    3    7      100
5       2    3    6      150
##part j ###
data1 %>%
  select(Week, MilkProd)
    Week MilkProd
1      0     1260
2      0     1900
3      0     1380
4      0     3910
5      0     2900
6      0     2210
7      0     1850
8      0     1750
9      0     1900
10     0     1950
11     0     1190
12     0     1190
13     0      590
14     0     1410
15     0     1320
16     0     4120
17     0     3530
18     0     1940
19     0     3130
20     0     3230
21     0     1480
22     0     2180
23     0     2610
24     0     2320
25     0     1740
26     0     1740
27     0     1680
28     0     1890
29     0     1970
30     0     2770
31     1     1640
32     1     2570
33     1     2760
34     1     3190
35     1     2440
36     1     2330
37     1      930
38     1     1810
39     1     1500
40     1     1800
41     1      760
42     1     1030
43     1      910
44     1      990
45     1      950
46     1     4810
47     1     3040
48     1     2000
49     1     2440
50     1     4040
51     1     1870
52     1     1700
53     1     1850
54     1     1420
55     1     1260
56     1     1190
57     1     1240
58     1     1380
59     1     1170
60     1     1790
61     2     1080
62     2     1100
63     2     1550
64     2     1050
65     2     1280
66     2     1700
67     2      850
68     2     1540
69     2      950
70     2     1350
71     2      540
72     2      700
73     2      600
74     2      750
75     2      700
76     2     1850
77     2     1380
78     2     1650
79     2     1230
80     2     1580
81     2     1500
82     2     1380
83     2     1120
84     2     1130
85     2      860
86     2      960
87     2     1080
88     2     1120
89     2      960
90     2     1020
91     3     1000
92     3     1520
93     3      980
94     3     1180
95     3     1540
96     3     1180
97     3      780
98     3     1210
99     3      500
100    3     1000
101    3      500
102    3      500
103    3      320
104    3      240
105    3      460
106    3     1600
107    3     1250
108    3     1420
109    3     1020
110    3     1450
111    3     1300
112    3     1100
113    3      750
114    3      900
115    3      640
116    3      600
117    3      980
118    3      940
119    3      750
120    3      570
121    4      950
122    4     1200
123    4     1380
124    4      980
125    4      740
126    4      890
127    4      380
128    4      810
129    4      260
130    4      800
131    4      370
132    4      350
133    4      250
134    4      170
135    4      380
136    4     1680
137    4     1200
138    4      960
139    4     1100
140    4      620
141    4      900
142    4      720
143    4      680
144    4      480
145    4      800
146    4      700
147    4      800
148    4      680
149    4      400
150    4      420
151    5     1000
152    5     1300
153    5     1000
154    5      850
155    5      800
156    5      850
157    5      300
158    5      600
159    5      300
160    5      650
161    5      250
162    5      250
163    5      200
164    5      100
165    5      270
166    5     1380
167    5      920
168    5     1280
169    5     1120
170    5      800
171    5      640
172    5      800
173    5      420
174    5      380
175    5      900
176    5      660
177    5      760
178    5      640
179    5      480
180    5      460
181    6      900
182    6     1350
183    6     1300
184    6     1100
185    6      600
186    6      750
187    6      560
188    6      750
189    6      250
190    6      600
191    6      360
192    6      300
193    6      150
194    6      200
195    6      200
196    6     1100
197    6      850
198    6     1100
199    6     1200
200    6      750
201    6      400
202    6      520
203    6      500
204    6      400
205    6      950
206    6      650
207    6      900
208    6      850
209    6      500
210    6      400
211    7      800
212    7     1250
213    7     1050
214    7      950
215    7      500
216    7      600
217    7      350
218    7      500
219    7      200
220    7      500
221    7      300
222    7      100
223    7      100
224    7      200
225    7      100
226    7     1000
227    7     1150
228    7     1120
229    7     1450
230    7      660
231    7      780
232    7      620
233    7      550
234    7      450
235    7     1000
236    7      550
237    7      820
238    7      520
239    7      630
240    7      500
##part k ###
data1 %>%
  select(-EweType)
    Diet Week MilkProd
1      1    0     1260
2      1    0     1900
3      1    0     1380
4      1    0     3910
5      1    0     2900
6      2    0     2210
7      2    0     1850
8      2    0     1750
9      2    0     1900
10     2    0     1950
11     3    0     1190
12     3    0     1190
13     3    0      590
14     3    0     1410
15     3    0     1320
16     1    0     4120
17     1    0     3530
18     1    0     1940
19     1    0     3130
20     1    0     3230
21     2    0     1480
22     2    0     2180
23     2    0     2610
24     2    0     2320
25     2    0     1740
26     3    0     1740
27     3    0     1680
28     3    0     1890
29     3    0     1970
30     3    0     2770
31     1    1     1640
32     1    1     2570
33     1    1     2760
34     1    1     3190
35     1    1     2440
36     2    1     2330
37     2    1      930
38     2    1     1810
39     2    1     1500
40     2    1     1800
41     3    1      760
42     3    1     1030
43     3    1      910
44     3    1      990
45     3    1      950
46     1    1     4810
47     1    1     3040
48     1    1     2000
49     1    1     2440
50     1    1     4040
51     2    1     1870
52     2    1     1700
53     2    1     1850
54     2    1     1420
55     2    1     1260
56     3    1     1190
57     3    1     1240
58     3    1     1380
59     3    1     1170
60     3    1     1790
61     1    2     1080
62     1    2     1100
63     1    2     1550
64     1    2     1050
65     1    2     1280
66     2    2     1700
67     2    2      850
68     2    2     1540
69     2    2      950
70     2    2     1350
71     3    2      540
72     3    2      700
73     3    2      600
74     3    2      750
75     3    2      700
76     1    2     1850
77     1    2     1380
78     1    2     1650
79     1    2     1230
80     1    2     1580
81     2    2     1500
82     2    2     1380
83     2    2     1120
84     2    2     1130
85     2    2      860
86     3    2      960
87     3    2     1080
88     3    2     1120
89     3    2      960
90     3    2     1020
91     1    3     1000
92     1    3     1520
93     1    3      980
94     1    3     1180
95     1    3     1540
96     2    3     1180
97     2    3      780
98     2    3     1210
99     2    3      500
100    2    3     1000
101    3    3      500
102    3    3      500
103    3    3      320
104    3    3      240
105    3    3      460
106    1    3     1600
107    1    3     1250
108    1    3     1420
109    1    3     1020
110    1    3     1450
111    2    3     1300
112    2    3     1100
113    2    3      750
114    2    3      900
115    2    3      640
116    3    3      600
117    3    3      980
118    3    3      940
119    3    3      750
120    3    3      570
121    1    4      950
122    1    4     1200
123    1    4     1380
124    1    4      980
125    1    4      740
126    2    4      890
127    2    4      380
128    2    4      810
129    2    4      260
130    2    4      800
131    3    4      370
132    3    4      350
133    3    4      250
134    3    4      170
135    3    4      380
136    1    4     1680
137    1    4     1200
138    1    4      960
139    1    4     1100
140    1    4      620
141    2    4      900
142    2    4      720
143    2    4      680
144    2    4      480
145    2    4      800
146    3    4      700
147    3    4      800
148    3    4      680
149    3    4      400
150    3    4      420
151    1    5     1000
152    1    5     1300
153    1    5     1000
154    1    5      850
155    1    5      800
156    2    5      850
157    2    5      300
158    2    5      600
159    2    5      300
160    2    5      650
161    3    5      250
162    3    5      250
163    3    5      200
164    3    5      100
165    3    5      270
166    1    5     1380
167    1    5      920
168    1    5     1280
169    1    5     1120
170    1    5      800
171    2    5      640
172    2    5      800
173    2    5      420
174    2    5      380
175    2    5      900
176    3    5      660
177    3    5      760
178    3    5      640
179    3    5      480
180    3    5      460
181    1    6      900
182    1    6     1350
183    1    6     1300
184    1    6     1100
185    1    6      600
186    2    6      750
187    2    6      560
188    2    6      750
189    2    6      250
190    2    6      600
191    3    6      360
192    3    6      300
193    3    6      150
194    3    6      200
195    3    6      200
196    1    6     1100
197    1    6      850
198    1    6     1100
199    1    6     1200
200    1    6      750
201    2    6      400
202    2    6      520
203    2    6      500
204    2    6      400
205    2    6      950
206    3    6      650
207    3    6      900
208    3    6      850
209    3    6      500
210    3    6      400
211    1    7      800
212    1    7     1250
213    1    7     1050
214    1    7      950
215    1    7      500
216    2    7      600
217    2    7      350
218    2    7      500
219    2    7      200
220    2    7      500
221    3    7      300
222    3    7      100
223    3    7      100
224    3    7      200
225    3    7      100
226    1    7     1000
227    1    7     1150
228    1    7     1120
229    1    7     1450
230    1    7      660
231    2    7      780
232    2    7      620
233    2    7      550
234    2    7      450
235    2    7     1000
236    3    7      550
237    3    7      820
238    3    7      520
239    3    7      630
240    3    7      500
##part l ###
data1 %>%
  rename(., GeneticLine = EweType)
    GeneticLine Diet Week MilkProd
1             2    1    0     1260
2             2    1    0     1900
3             2    1    0     1380
4             2    1    0     3910
5             2    1    0     2900
6             2    2    0     2210
7             2    2    0     1850
8             2    2    0     1750
9             2    2    0     1900
10            2    2    0     1950
11            2    3    0     1190
12            2    3    0     1190
13            2    3    0      590
14            2    3    0     1410
15            2    3    0     1320
16            1    1    0     4120
17            1    1    0     3530
18            1    1    0     1940
19            1    1    0     3130
20            1    1    0     3230
21            1    2    0     1480
22            1    2    0     2180
23            1    2    0     2610
24            1    2    0     2320
25            1    2    0     1740
26            1    3    0     1740
27            1    3    0     1680
28            1    3    0     1890
29            1    3    0     1970
30            1    3    0     2770
31            2    1    1     1640
32            2    1    1     2570
33            2    1    1     2760
34            2    1    1     3190
35            2    1    1     2440
36            2    2    1     2330
37            2    2    1      930
38            2    2    1     1810
39            2    2    1     1500
40            2    2    1     1800
41            2    3    1      760
42            2    3    1     1030
43            2    3    1      910
44            2    3    1      990
45            2    3    1      950
46            1    1    1     4810
47            1    1    1     3040
48            1    1    1     2000
49            1    1    1     2440
50            1    1    1     4040
51            1    2    1     1870
52            1    2    1     1700
53            1    2    1     1850
54            1    2    1     1420
55            1    2    1     1260
56            1    3    1     1190
57            1    3    1     1240
58            1    3    1     1380
59            1    3    1     1170
60            1    3    1     1790
61            2    1    2     1080
62            2    1    2     1100
63            2    1    2     1550
64            2    1    2     1050
65            2    1    2     1280
66            2    2    2     1700
67            2    2    2      850
68            2    2    2     1540
69            2    2    2      950
70            2    2    2     1350
71            2    3    2      540
72            2    3    2      700
73            2    3    2      600
74            2    3    2      750
75            2    3    2      700
76            1    1    2     1850
77            1    1    2     1380
78            1    1    2     1650
79            1    1    2     1230
80            1    1    2     1580
81            1    2    2     1500
82            1    2    2     1380
83            1    2    2     1120
84            1    2    2     1130
85            1    2    2      860
86            1    3    2      960
87            1    3    2     1080
88            1    3    2     1120
89            1    3    2      960
90            1    3    2     1020
91            2    1    3     1000
92            2    1    3     1520
93            2    1    3      980
94            2    1    3     1180
95            2    1    3     1540
96            2    2    3     1180
97            2    2    3      780
98            2    2    3     1210
99            2    2    3      500
100           2    2    3     1000
101           2    3    3      500
102           2    3    3      500
103           2    3    3      320
104           2    3    3      240
105           2    3    3      460
106           1    1    3     1600
107           1    1    3     1250
108           1    1    3     1420
109           1    1    3     1020
110           1    1    3     1450
111           1    2    3     1300
112           1    2    3     1100
113           1    2    3      750
114           1    2    3      900
115           1    2    3      640
116           1    3    3      600
117           1    3    3      980
118           1    3    3      940
119           1    3    3      750
120           1    3    3      570
121           2    1    4      950
122           2    1    4     1200
123           2    1    4     1380
124           2    1    4      980
125           2    1    4      740
126           2    2    4      890
127           2    2    4      380
128           2    2    4      810
129           2    2    4      260
130           2    2    4      800
131           2    3    4      370
132           2    3    4      350
133           2    3    4      250
134           2    3    4      170
135           2    3    4      380
136           1    1    4     1680
137           1    1    4     1200
138           1    1    4      960
139           1    1    4     1100
140           1    1    4      620
141           1    2    4      900
142           1    2    4      720
143           1    2    4      680
144           1    2    4      480
145           1    2    4      800
146           1    3    4      700
147           1    3    4      800
148           1    3    4      680
149           1    3    4      400
150           1    3    4      420
151           2    1    5     1000
152           2    1    5     1300
153           2    1    5     1000
154           2    1    5      850
155           2    1    5      800
156           2    2    5      850
157           2    2    5      300
158           2    2    5      600
159           2    2    5      300
160           2    2    5      650
161           2    3    5      250
162           2    3    5      250
163           2    3    5      200
164           2    3    5      100
165           2    3    5      270
166           1    1    5     1380
167           1    1    5      920
168           1    1    5     1280
169           1    1    5     1120
170           1    1    5      800
171           1    2    5      640
172           1    2    5      800
173           1    2    5      420
174           1    2    5      380
175           1    2    5      900
176           1    3    5      660
177           1    3    5      760
178           1    3    5      640
179           1    3    5      480
180           1    3    5      460
181           2    1    6      900
182           2    1    6     1350
183           2    1    6     1300
184           2    1    6     1100
185           2    1    6      600
186           2    2    6      750
187           2    2    6      560
188           2    2    6      750
189           2    2    6      250
190           2    2    6      600
191           2    3    6      360
192           2    3    6      300
193           2    3    6      150
194           2    3    6      200
195           2    3    6      200
196           1    1    6     1100
197           1    1    6      850
198           1    1    6     1100
199           1    1    6     1200
200           1    1    6      750
201           1    2    6      400
202           1    2    6      520
203           1    2    6      500
204           1    2    6      400
205           1    2    6      950
206           1    3    6      650
207           1    3    6      900
208           1    3    6      850
209           1    3    6      500
210           1    3    6      400
211           2    1    7      800
212           2    1    7     1250
213           2    1    7     1050
214           2    1    7      950
215           2    1    7      500
216           2    2    7      600
217           2    2    7      350
218           2    2    7      500
219           2    2    7      200
220           2    2    7      500
221           2    3    7      300
222           2    3    7      100
223           2    3    7      100
224           2    3    7      200
225           2    3    7      100
226           1    1    7     1000
227           1    1    7     1150
228           1    1    7     1120
229           1    1    7     1450
230           1    1    7      660
231           1    2    7      780
232           1    2    7      620
233           1    2    7      550
234           1    2    7      450
235           1    2    7     1000
236           1    3    7      550
237           1    3    7      820
238           1    3    7      520
239           1    3    7      630
240           1    3    7      500

You can add options to executable code like this

library(tidyverse)
library(car)
data2 <- read.csv("Liveweight.csv", colClasses = c(NA, "numeric"))
head(data2)
  Ewetype Diet Week LiveWeigth
1       1    1    0       67.5
2       1    1    0       86.0
3       1    1    0       85.5
4       1    1    0       74.5
5       1    1    0       84.0
6       1    2    0       80.0
str(data2)
'data.frame':   240 obs. of  4 variables:
 $ Ewetype   : int  1 1 1 1 1 1 1 1 1 1 ...
 $ Diet      : num  1 1 1 1 1 2 2 2 2 2 ...
 $ Week      : int  0 0 0 0 0 0 0 0 0 0 ...
 $ LiveWeigth: num  67.5 86 85.5 74.5 84 80 76.5 71.5 75 78.5 ...
glimpse(data2)
Rows: 240
Columns: 4
$ Ewetype    <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2,~
$ Diet       <dbl> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1,~
$ Week       <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
$ LiveWeigth <dbl> 67.5, 86.0, 85.5, 74.5, 84.0, 80.0, 76.5, 71.5, 75.0, 78.5,~
data2$Ewetype<- as.factor(data2$Ewetype)
data2$Diet<- as.factor(data2$Diet)
data2$Week <- as.character(data2$Week)
data2$LiveWeigth<- as.numeric(data2$LiveWeigth)
tail(data2)
    Ewetype Diet Week LiveWeigth
235       2    2    7       63.0
236       2    3    7       57.5
237       2    3    7       62.5
238       2    3    7       62.5
239       2    3    7       83.5
240       2    3    7       80.0
data2
    Ewetype Diet Week LiveWeigth
1         1    1    0       67.5
2         1    1    0       86.0
3         1    1    0       85.5
4         1    1    0       74.5
5         1    1    0       84.0
6         1    2    0       80.0
7         1    2    0       76.5
8         1    2    0       71.5
9         1    2    0       75.0
10        1    2    0       78.5
11        1    3    0       70.0
12        1    3    0       93.5
13        1    3    0       77.5
14        1    3    0       91.5
15        1    3    0       83.5
16        2    1    0       79.5
17        2    1    0       88.5
18        2    1    0       76.5
19        2    1    0       59.5
20        2    1    0       90.5
21        2    2    0       87.5
22        2    2    0       70.0
23        2    2    0       72.0
24        2    2    0       64.0
25        2    2    0       62.5
26        2    3    0       55.5
27        2    3    0       65.0
28        2    3    0       64.0
29        2    3    0       81.0
30        2    3    0       81.5
31        1    1    1       68.0
32        1    1    1       88.0
33        1    1    1       87.0
34        1    1    1       77.5
35        1    1    1       85.5
36        1    2    1       81.0
37        1    2    1       71.0
38        1    2    1       72.0
39        1    2    1       75.5
40        1    2    1       81.0
41        1    3    1       66.5
42        1    3    1       89.0
43        1    3    1       74.0
44        1    3    1       86.5
45        1    3    1       75.5
46        2    1    1       82.5
47        2    1    1       89.5
48        2    1    1       77.0
49        2    1    1       62.5
50        2    1    1       91.0
51        2    2    1       85.5
52        2    2    1       69.5
53        2    2    1       70.5
54        2    2    1       63.0
55        2    2    1       62.0
56        2    3    1       54.5
57        2    3    1       64.0
58        2    3    1       63.5
59        2    3    1       78.5
60        2    3    1       81.0
61        1    1    2       68.0
62        1    1    2       90.0
63        1    1    2       88.0
64        1    1    2       80.5
65        1    1    2       87.5
66        1    2    2       81.0
67        1    2    2       67.5
68        1    2    2       72.0
69        1    2    2       75.5
70        1    2    2       82.5
71        1    3    2       62.0
72        1    3    2       85.5
73        1    3    2       70.0
74        1    3    2       78.5
75        1    3    2       69.5
76        2    1    2       86.0
77        2    1    2       88.0
78        2    1    2       77.0
79        2    1    2       64.0
80        2    1    2       91.0
81        2    2    2       84.5
82        2    2    2       68.0
83        2    2    2       67.0
84        2    2    2       62.0
85        2    2    2       60.5
86        2    3    2       55.0
87        2    3    2       62.5
88        2    3    2       64.0
89        2    3    2       77.0
90        2    3    2       80.0
91        1    1    3       66.5
92        1    1    3       89.5
93        1    1    3       87.0
94        1    1    3       84.0
95        1    1    3       89.5
96        1    2    3       80.0
97        1    2    3       67.5
98        1    2    3       69.0
99        1    2    3       77.0
100       1    2    3       82.0
101       1    3    3       63.0
102       1    3    3       83.5
103       1    3    3       73.5
104       1    3    3       76.5
105       1    3    3       71.0
106       2    1    3       94.5
107       2    1    3       88.0
108       2    1    3       77.5
109       2    1    3       66.0
110       2    1    3       92.0
111       2    2    3       83.0
112       2    2    3       67.0
113       2    2    3       65.5
114       2    2    3       61.5
115       2    2    3       61.0
116       2    3    3       54.5
117       2    3    3       61.0
118       2    3    3       62.5
119       2    3    3       75.5
120       2    3    3       80.5
121       1    1    4       69.5
122       1    1    4       90.0
123       1    1    4       82.0
124       1    1    4       86.0
125       1    1    4       89.0
126       1    2    4       82.5
127       1    2    4       71.0
128       1    2    4       70.5
129       1    2    4       79.5
130       1    2    4       80.5
131       1    3    4       63.5
132       1    3    4       84.0
133       1    3    4       75.5
134       1    3    4       75.0
135       1    3    4       76.0
136       2    1    4       83.5
137       2    1    4       86.0
138       2    1    4       78.0
139       2    1    4       64.5
140       2    1    4       90.5
141       2    2    4       82.5
142       2    2    4       68.0
143       2    2    4       64.5
144       2    2    4       62.5
145       2    2    4       61.5
146       2    3    4       53.5
147       2    3    4       61.0
148       2    3    4       62.5
149       2    3    4       75.5
150       2    3    4       80.5
151       1    1    5       69.5
152       1    1    5       87.5
153       1    1    5       80.5
154       1    1    5       83.0
155       1    1    5       83.0
156       1    2    5       80.0
157       1    2    5       71.5
158       1    2    5       71.5
159       1    2    5       80.0
160       1    2    5       79.5
161       1    3    5       61.0
162       1    3    5       81.5
163       1    3    5       71.0
164       1    3    5       71.0
165       1    3    5       70.0
166       2    1    5       81.5
167       2    1    5       83.5
168       2    1    5       73.5
169       2    1    5       61.5
170       2    1    5       87.5
171       2    2    5       80.5
172       2    2    5       65.0
173       2    2    5       59.5
174       2    2    5       60.0
175       2    2    5       60.0
176       2    3    5       52.0
177       2    3    5       59.0
178       2    3    5       61.5
179       2    3    5       75.0
180       2    3    5       79.0
181       1    1    6       72.0
182       1    1    6       92.5
183       1    1    6       84.0
184       1    1    6       88.0
185       1    1    6       87.5
186       1    2    6       82.0
187       1    2    6       74.0
188       1    2    6       74.0
189       1    2    6       83.0
190       1    2    6       81.0
191       1    3    6       63.0
192       1    3    6       82.5
193       1    3    6       75.0
194       1    3    6       72.0
195       1    3    6       75.0
196       2    1    6       85.5
197       2    1    6       89.5
198       2    1    6       79.5
199       2    1    6       63.0
200       2    1    6       94.5
201       2    2    6       85.5
202       2    2    6       68.5
203       2    2    6       60.5
204       2    2    6       65.5
205       2    2    6       62.0
206       2    3    6       54.5
207       2    3    6       61.0
208       2    3    6       62.0
209       2    3    6       80.0
210       2    3    6       79.0
211       1    1    7       77.5
212       1    1    7       98.5
213       1    1    7       88.5
214       1    1    7       92.5
215       1    1    7       92.0
216       1    2    7       85.0
217       1    2    7       77.5
218       1    2    7       77.5
219       1    2    7       85.0
220       1    2    7       82.0
221       1    3    7       67.5
222       1    3    7       83.5
223       1    3    7       81.0
224       1    3    7       72.5
225       1    3    7       76.5
226       2    1    7       93.5
227       2    1    7       94.5
228       2    1    7       85.0
229       2    1    7       64.5
230       2    1    7       99.5
231       2    2    7       90.0
232       2    2    7       72.0
233       2    2    7       62.0
234       2    2    7       70.0
235       2    2    7       63.0
236       2    3    7       57.5
237       2    3    7       62.5
238       2    3    7       62.5
239       2    3    7       83.5
240       2    3    7       80.0
###Question 2####
library(dplyr)
data2 %>%
  group_by(Week)
# A tibble: 240 x 4
# Groups:   Week [8]
   Ewetype Diet  Week  LiveWeigth
   <fct>   <fct> <chr>      <dbl>
 1 1       1     0           67.5
 2 1       1     0           86  
 3 1       1     0           85.5
 4 1       1     0           74.5
 5 1       1     0           84  
 6 1       2     0           80  
 7 1       2     0           76.5
 8 1       2     0           71.5
 9 1       2     0           75  
10 1       2     0           78.5
# i 230 more rows
# Part A
data2 %>%
  select(Week)%>%
  mutate(
    Early = Week %in% c(0,1,2),
    Late = if_else(Week %in% c(0, 1, 2), "Early", "Late")
  )
    Week Early  Late
1      0  TRUE Early
2      0  TRUE Early
3      0  TRUE Early
4      0  TRUE Early
5      0  TRUE Early
6      0  TRUE Early
7      0  TRUE Early
8      0  TRUE Early
9      0  TRUE Early
10     0  TRUE Early
11     0  TRUE Early
12     0  TRUE Early
13     0  TRUE Early
14     0  TRUE Early
15     0  TRUE Early
16     0  TRUE Early
17     0  TRUE Early
18     0  TRUE Early
19     0  TRUE Early
20     0  TRUE Early
21     0  TRUE Early
22     0  TRUE Early
23     0  TRUE Early
24     0  TRUE Early
25     0  TRUE Early
26     0  TRUE Early
27     0  TRUE Early
28     0  TRUE Early
29     0  TRUE Early
30     0  TRUE Early
31     1  TRUE Early
32     1  TRUE Early
33     1  TRUE Early
34     1  TRUE Early
35     1  TRUE Early
36     1  TRUE Early
37     1  TRUE Early
38     1  TRUE Early
39     1  TRUE Early
40     1  TRUE Early
41     1  TRUE Early
42     1  TRUE Early
43     1  TRUE Early
44     1  TRUE Early
45     1  TRUE Early
46     1  TRUE Early
47     1  TRUE Early
48     1  TRUE Early
49     1  TRUE Early
50     1  TRUE Early
51     1  TRUE Early
52     1  TRUE Early
53     1  TRUE Early
54     1  TRUE Early
55     1  TRUE Early
56     1  TRUE Early
57     1  TRUE Early
58     1  TRUE Early
59     1  TRUE Early
60     1  TRUE Early
61     2  TRUE Early
62     2  TRUE Early
63     2  TRUE Early
64     2  TRUE Early
65     2  TRUE Early
66     2  TRUE Early
67     2  TRUE Early
68     2  TRUE Early
69     2  TRUE Early
70     2  TRUE Early
71     2  TRUE Early
72     2  TRUE Early
73     2  TRUE Early
74     2  TRUE Early
75     2  TRUE Early
76     2  TRUE Early
77     2  TRUE Early
78     2  TRUE Early
79     2  TRUE Early
80     2  TRUE Early
81     2  TRUE Early
82     2  TRUE Early
83     2  TRUE Early
84     2  TRUE Early
85     2  TRUE Early
86     2  TRUE Early
87     2  TRUE Early
88     2  TRUE Early
89     2  TRUE Early
90     2  TRUE Early
91     3 FALSE  Late
92     3 FALSE  Late
93     3 FALSE  Late
94     3 FALSE  Late
95     3 FALSE  Late
96     3 FALSE  Late
97     3 FALSE  Late
98     3 FALSE  Late
99     3 FALSE  Late
100    3 FALSE  Late
101    3 FALSE  Late
102    3 FALSE  Late
103    3 FALSE  Late
104    3 FALSE  Late
105    3 FALSE  Late
106    3 FALSE  Late
107    3 FALSE  Late
108    3 FALSE  Late
109    3 FALSE  Late
110    3 FALSE  Late
111    3 FALSE  Late
112    3 FALSE  Late
113    3 FALSE  Late
114    3 FALSE  Late
115    3 FALSE  Late
116    3 FALSE  Late
117    3 FALSE  Late
118    3 FALSE  Late
119    3 FALSE  Late
120    3 FALSE  Late
121    4 FALSE  Late
122    4 FALSE  Late
123    4 FALSE  Late
124    4 FALSE  Late
125    4 FALSE  Late
126    4 FALSE  Late
127    4 FALSE  Late
128    4 FALSE  Late
129    4 FALSE  Late
130    4 FALSE  Late
131    4 FALSE  Late
132    4 FALSE  Late
133    4 FALSE  Late
134    4 FALSE  Late
135    4 FALSE  Late
136    4 FALSE  Late
137    4 FALSE  Late
138    4 FALSE  Late
139    4 FALSE  Late
140    4 FALSE  Late
141    4 FALSE  Late
142    4 FALSE  Late
143    4 FALSE  Late
144    4 FALSE  Late
145    4 FALSE  Late
146    4 FALSE  Late
147    4 FALSE  Late
148    4 FALSE  Late
149    4 FALSE  Late
150    4 FALSE  Late
151    5 FALSE  Late
152    5 FALSE  Late
153    5 FALSE  Late
154    5 FALSE  Late
155    5 FALSE  Late
156    5 FALSE  Late
157    5 FALSE  Late
158    5 FALSE  Late
159    5 FALSE  Late
160    5 FALSE  Late
161    5 FALSE  Late
162    5 FALSE  Late
163    5 FALSE  Late
164    5 FALSE  Late
165    5 FALSE  Late
166    5 FALSE  Late
167    5 FALSE  Late
168    5 FALSE  Late
169    5 FALSE  Late
170    5 FALSE  Late
171    5 FALSE  Late
172    5 FALSE  Late
173    5 FALSE  Late
174    5 FALSE  Late
175    5 FALSE  Late
176    5 FALSE  Late
177    5 FALSE  Late
178    5 FALSE  Late
179    5 FALSE  Late
180    5 FALSE  Late
181    6 FALSE  Late
182    6 FALSE  Late
183    6 FALSE  Late
184    6 FALSE  Late
185    6 FALSE  Late
186    6 FALSE  Late
187    6 FALSE  Late
188    6 FALSE  Late
189    6 FALSE  Late
190    6 FALSE  Late
191    6 FALSE  Late
192    6 FALSE  Late
193    6 FALSE  Late
194    6 FALSE  Late
195    6 FALSE  Late
196    6 FALSE  Late
197    6 FALSE  Late
198    6 FALSE  Late
199    6 FALSE  Late
200    6 FALSE  Late
201    6 FALSE  Late
202    6 FALSE  Late
203    6 FALSE  Late
204    6 FALSE  Late
205    6 FALSE  Late
206    6 FALSE  Late
207    6 FALSE  Late
208    6 FALSE  Late
209    6 FALSE  Late
210    6 FALSE  Late
211    7 FALSE  Late
212    7 FALSE  Late
213    7 FALSE  Late
214    7 FALSE  Late
215    7 FALSE  Late
216    7 FALSE  Late
217    7 FALSE  Late
218    7 FALSE  Late
219    7 FALSE  Late
220    7 FALSE  Late
221    7 FALSE  Late
222    7 FALSE  Late
223    7 FALSE  Late
224    7 FALSE  Late
225    7 FALSE  Late
226    7 FALSE  Late
227    7 FALSE  Late
228    7 FALSE  Late
229    7 FALSE  Late
230    7 FALSE  Late
231    7 FALSE  Late
232    7 FALSE  Late
233    7 FALSE  Late
234    7 FALSE  Late
235    7 FALSE  Late
236    7 FALSE  Late
237    7 FALSE  Late
238    7 FALSE  Late
239    7 FALSE  Late
240    7 FALSE  Late
#Part B
data2 %>%
  mutate(LiveWeigth75kg = ifelse(LiveWeigth > 75, "Above", "Below"))
    Ewetype Diet Week LiveWeigth LiveWeigth75kg
1         1    1    0       67.5          Below
2         1    1    0       86.0          Above
3         1    1    0       85.5          Above
4         1    1    0       74.5          Below
5         1    1    0       84.0          Above
6         1    2    0       80.0          Above
7         1    2    0       76.5          Above
8         1    2    0       71.5          Below
9         1    2    0       75.0          Below
10        1    2    0       78.5          Above
11        1    3    0       70.0          Below
12        1    3    0       93.5          Above
13        1    3    0       77.5          Above
14        1    3    0       91.5          Above
15        1    3    0       83.5          Above
16        2    1    0       79.5          Above
17        2    1    0       88.5          Above
18        2    1    0       76.5          Above
19        2    1    0       59.5          Below
20        2    1    0       90.5          Above
21        2    2    0       87.5          Above
22        2    2    0       70.0          Below
23        2    2    0       72.0          Below
24        2    2    0       64.0          Below
25        2    2    0       62.5          Below
26        2    3    0       55.5          Below
27        2    3    0       65.0          Below
28        2    3    0       64.0          Below
29        2    3    0       81.0          Above
30        2    3    0       81.5          Above
31        1    1    1       68.0          Below
32        1    1    1       88.0          Above
33        1    1    1       87.0          Above
34        1    1    1       77.5          Above
35        1    1    1       85.5          Above
36        1    2    1       81.0          Above
37        1    2    1       71.0          Below
38        1    2    1       72.0          Below
39        1    2    1       75.5          Above
40        1    2    1       81.0          Above
41        1    3    1       66.5          Below
42        1    3    1       89.0          Above
43        1    3    1       74.0          Below
44        1    3    1       86.5          Above
45        1    3    1       75.5          Above
46        2    1    1       82.5          Above
47        2    1    1       89.5          Above
48        2    1    1       77.0          Above
49        2    1    1       62.5          Below
50        2    1    1       91.0          Above
51        2    2    1       85.5          Above
52        2    2    1       69.5          Below
53        2    2    1       70.5          Below
54        2    2    1       63.0          Below
55        2    2    1       62.0          Below
56        2    3    1       54.5          Below
57        2    3    1       64.0          Below
58        2    3    1       63.5          Below
59        2    3    1       78.5          Above
60        2    3    1       81.0          Above
61        1    1    2       68.0          Below
62        1    1    2       90.0          Above
63        1    1    2       88.0          Above
64        1    1    2       80.5          Above
65        1    1    2       87.5          Above
66        1    2    2       81.0          Above
67        1    2    2       67.5          Below
68        1    2    2       72.0          Below
69        1    2    2       75.5          Above
70        1    2    2       82.5          Above
71        1    3    2       62.0          Below
72        1    3    2       85.5          Above
73        1    3    2       70.0          Below
74        1    3    2       78.5          Above
75        1    3    2       69.5          Below
76        2    1    2       86.0          Above
77        2    1    2       88.0          Above
78        2    1    2       77.0          Above
79        2    1    2       64.0          Below
80        2    1    2       91.0          Above
81        2    2    2       84.5          Above
82        2    2    2       68.0          Below
83        2    2    2       67.0          Below
84        2    2    2       62.0          Below
85        2    2    2       60.5          Below
86        2    3    2       55.0          Below
87        2    3    2       62.5          Below
88        2    3    2       64.0          Below
89        2    3    2       77.0          Above
90        2    3    2       80.0          Above
91        1    1    3       66.5          Below
92        1    1    3       89.5          Above
93        1    1    3       87.0          Above
94        1    1    3       84.0          Above
95        1    1    3       89.5          Above
96        1    2    3       80.0          Above
97        1    2    3       67.5          Below
98        1    2    3       69.0          Below
99        1    2    3       77.0          Above
100       1    2    3       82.0          Above
101       1    3    3       63.0          Below
102       1    3    3       83.5          Above
103       1    3    3       73.5          Below
104       1    3    3       76.5          Above
105       1    3    3       71.0          Below
106       2    1    3       94.5          Above
107       2    1    3       88.0          Above
108       2    1    3       77.5          Above
109       2    1    3       66.0          Below
110       2    1    3       92.0          Above
111       2    2    3       83.0          Above
112       2    2    3       67.0          Below
113       2    2    3       65.5          Below
114       2    2    3       61.5          Below
115       2    2    3       61.0          Below
116       2    3    3       54.5          Below
117       2    3    3       61.0          Below
118       2    3    3       62.5          Below
119       2    3    3       75.5          Above
120       2    3    3       80.5          Above
121       1    1    4       69.5          Below
122       1    1    4       90.0          Above
123       1    1    4       82.0          Above
124       1    1    4       86.0          Above
125       1    1    4       89.0          Above
126       1    2    4       82.5          Above
127       1    2    4       71.0          Below
128       1    2    4       70.5          Below
129       1    2    4       79.5          Above
130       1    2    4       80.5          Above
131       1    3    4       63.5          Below
132       1    3    4       84.0          Above
133       1    3    4       75.5          Above
134       1    3    4       75.0          Below
135       1    3    4       76.0          Above
136       2    1    4       83.5          Above
137       2    1    4       86.0          Above
138       2    1    4       78.0          Above
139       2    1    4       64.5          Below
140       2    1    4       90.5          Above
141       2    2    4       82.5          Above
142       2    2    4       68.0          Below
143       2    2    4       64.5          Below
144       2    2    4       62.5          Below
145       2    2    4       61.5          Below
146       2    3    4       53.5          Below
147       2    3    4       61.0          Below
148       2    3    4       62.5          Below
149       2    3    4       75.5          Above
150       2    3    4       80.5          Above
151       1    1    5       69.5          Below
152       1    1    5       87.5          Above
153       1    1    5       80.5          Above
154       1    1    5       83.0          Above
155       1    1    5       83.0          Above
156       1    2    5       80.0          Above
157       1    2    5       71.5          Below
158       1    2    5       71.5          Below
159       1    2    5       80.0          Above
160       1    2    5       79.5          Above
161       1    3    5       61.0          Below
162       1    3    5       81.5          Above
163       1    3    5       71.0          Below
164       1    3    5       71.0          Below
165       1    3    5       70.0          Below
166       2    1    5       81.5          Above
167       2    1    5       83.5          Above
168       2    1    5       73.5          Below
169       2    1    5       61.5          Below
170       2    1    5       87.5          Above
171       2    2    5       80.5          Above
172       2    2    5       65.0          Below
173       2    2    5       59.5          Below
174       2    2    5       60.0          Below
175       2    2    5       60.0          Below
176       2    3    5       52.0          Below
177       2    3    5       59.0          Below
178       2    3    5       61.5          Below
179       2    3    5       75.0          Below
180       2    3    5       79.0          Above
181       1    1    6       72.0          Below
182       1    1    6       92.5          Above
183       1    1    6       84.0          Above
184       1    1    6       88.0          Above
185       1    1    6       87.5          Above
186       1    2    6       82.0          Above
187       1    2    6       74.0          Below
188       1    2    6       74.0          Below
189       1    2    6       83.0          Above
190       1    2    6       81.0          Above
191       1    3    6       63.0          Below
192       1    3    6       82.5          Above
193       1    3    6       75.0          Below
194       1    3    6       72.0          Below
195       1    3    6       75.0          Below
196       2    1    6       85.5          Above
197       2    1    6       89.5          Above
198       2    1    6       79.5          Above
199       2    1    6       63.0          Below
200       2    1    6       94.5          Above
201       2    2    6       85.5          Above
202       2    2    6       68.5          Below
203       2    2    6       60.5          Below
204       2    2    6       65.5          Below
205       2    2    6       62.0          Below
206       2    3    6       54.5          Below
207       2    3    6       61.0          Below
208       2    3    6       62.0          Below
209       2    3    6       80.0          Above
210       2    3    6       79.0          Above
211       1    1    7       77.5          Above
212       1    1    7       98.5          Above
213       1    1    7       88.5          Above
214       1    1    7       92.5          Above
215       1    1    7       92.0          Above
216       1    2    7       85.0          Above
217       1    2    7       77.5          Above
218       1    2    7       77.5          Above
219       1    2    7       85.0          Above
220       1    2    7       82.0          Above
221       1    3    7       67.5          Below
222       1    3    7       83.5          Above
223       1    3    7       81.0          Above
224       1    3    7       72.5          Below
225       1    3    7       76.5          Above
226       2    1    7       93.5          Above
227       2    1    7       94.5          Above
228       2    1    7       85.0          Above
229       2    1    7       64.5          Below
230       2    1    7       99.5          Above
231       2    2    7       90.0          Above
232       2    2    7       72.0          Below
233       2    2    7       62.0          Below
234       2    2    7       70.0          Below
235       2    2    7       63.0          Below
236       2    3    7       57.5          Below
237       2    3    7       62.5          Below
238       2    3    7       62.5          Below
239       2    3    7       83.5          Above
240       2    3    7       80.0          Above
#Part C and D
data2 %>%
  mutate(
      (LiveWeigth/1000) *2.2,)
    Ewetype Diet Week LiveWeigth (LiveWeigth/1000) * 2.2
1         1    1    0       67.5                  0.1485
2         1    1    0       86.0                  0.1892
3         1    1    0       85.5                  0.1881
4         1    1    0       74.5                  0.1639
5         1    1    0       84.0                  0.1848
6         1    2    0       80.0                  0.1760
7         1    2    0       76.5                  0.1683
8         1    2    0       71.5                  0.1573
9         1    2    0       75.0                  0.1650
10        1    2    0       78.5                  0.1727
11        1    3    0       70.0                  0.1540
12        1    3    0       93.5                  0.2057
13        1    3    0       77.5                  0.1705
14        1    3    0       91.5                  0.2013
15        1    3    0       83.5                  0.1837
16        2    1    0       79.5                  0.1749
17        2    1    0       88.5                  0.1947
18        2    1    0       76.5                  0.1683
19        2    1    0       59.5                  0.1309
20        2    1    0       90.5                  0.1991
21        2    2    0       87.5                  0.1925
22        2    2    0       70.0                  0.1540
23        2    2    0       72.0                  0.1584
24        2    2    0       64.0                  0.1408
25        2    2    0       62.5                  0.1375
26        2    3    0       55.5                  0.1221
27        2    3    0       65.0                  0.1430
28        2    3    0       64.0                  0.1408
29        2    3    0       81.0                  0.1782
30        2    3    0       81.5                  0.1793
31        1    1    1       68.0                  0.1496
32        1    1    1       88.0                  0.1936
33        1    1    1       87.0                  0.1914
34        1    1    1       77.5                  0.1705
35        1    1    1       85.5                  0.1881
36        1    2    1       81.0                  0.1782
37        1    2    1       71.0                  0.1562
38        1    2    1       72.0                  0.1584
39        1    2    1       75.5                  0.1661
40        1    2    1       81.0                  0.1782
41        1    3    1       66.5                  0.1463
42        1    3    1       89.0                  0.1958
43        1    3    1       74.0                  0.1628
44        1    3    1       86.5                  0.1903
45        1    3    1       75.5                  0.1661
46        2    1    1       82.5                  0.1815
47        2    1    1       89.5                  0.1969
48        2    1    1       77.0                  0.1694
49        2    1    1       62.5                  0.1375
50        2    1    1       91.0                  0.2002
51        2    2    1       85.5                  0.1881
52        2    2    1       69.5                  0.1529
53        2    2    1       70.5                  0.1551
54        2    2    1       63.0                  0.1386
55        2    2    1       62.0                  0.1364
56        2    3    1       54.5                  0.1199
57        2    3    1       64.0                  0.1408
58        2    3    1       63.5                  0.1397
59        2    3    1       78.5                  0.1727
60        2    3    1       81.0                  0.1782
61        1    1    2       68.0                  0.1496
62        1    1    2       90.0                  0.1980
63        1    1    2       88.0                  0.1936
64        1    1    2       80.5                  0.1771
65        1    1    2       87.5                  0.1925
66        1    2    2       81.0                  0.1782
67        1    2    2       67.5                  0.1485
68        1    2    2       72.0                  0.1584
69        1    2    2       75.5                  0.1661
70        1    2    2       82.5                  0.1815
71        1    3    2       62.0                  0.1364
72        1    3    2       85.5                  0.1881
73        1    3    2       70.0                  0.1540
74        1    3    2       78.5                  0.1727
75        1    3    2       69.5                  0.1529
76        2    1    2       86.0                  0.1892
77        2    1    2       88.0                  0.1936
78        2    1    2       77.0                  0.1694
79        2    1    2       64.0                  0.1408
80        2    1    2       91.0                  0.2002
81        2    2    2       84.5                  0.1859
82        2    2    2       68.0                  0.1496
83        2    2    2       67.0                  0.1474
84        2    2    2       62.0                  0.1364
85        2    2    2       60.5                  0.1331
86        2    3    2       55.0                  0.1210
87        2    3    2       62.5                  0.1375
88        2    3    2       64.0                  0.1408
89        2    3    2       77.0                  0.1694
90        2    3    2       80.0                  0.1760
91        1    1    3       66.5                  0.1463
92        1    1    3       89.5                  0.1969
93        1    1    3       87.0                  0.1914
94        1    1    3       84.0                  0.1848
95        1    1    3       89.5                  0.1969
96        1    2    3       80.0                  0.1760
97        1    2    3       67.5                  0.1485
98        1    2    3       69.0                  0.1518
99        1    2    3       77.0                  0.1694
100       1    2    3       82.0                  0.1804
101       1    3    3       63.0                  0.1386
102       1    3    3       83.5                  0.1837
103       1    3    3       73.5                  0.1617
104       1    3    3       76.5                  0.1683
105       1    3    3       71.0                  0.1562
106       2    1    3       94.5                  0.2079
107       2    1    3       88.0                  0.1936
108       2    1    3       77.5                  0.1705
109       2    1    3       66.0                  0.1452
110       2    1    3       92.0                  0.2024
111       2    2    3       83.0                  0.1826
112       2    2    3       67.0                  0.1474
113       2    2    3       65.5                  0.1441
114       2    2    3       61.5                  0.1353
115       2    2    3       61.0                  0.1342
116       2    3    3       54.5                  0.1199
117       2    3    3       61.0                  0.1342
118       2    3    3       62.5                  0.1375
119       2    3    3       75.5                  0.1661
120       2    3    3       80.5                  0.1771
121       1    1    4       69.5                  0.1529
122       1    1    4       90.0                  0.1980
123       1    1    4       82.0                  0.1804
124       1    1    4       86.0                  0.1892
125       1    1    4       89.0                  0.1958
126       1    2    4       82.5                  0.1815
127       1    2    4       71.0                  0.1562
128       1    2    4       70.5                  0.1551
129       1    2    4       79.5                  0.1749
130       1    2    4       80.5                  0.1771
131       1    3    4       63.5                  0.1397
132       1    3    4       84.0                  0.1848
133       1    3    4       75.5                  0.1661
134       1    3    4       75.0                  0.1650
135       1    3    4       76.0                  0.1672
136       2    1    4       83.5                  0.1837
137       2    1    4       86.0                  0.1892
138       2    1    4       78.0                  0.1716
139       2    1    4       64.5                  0.1419
140       2    1    4       90.5                  0.1991
141       2    2    4       82.5                  0.1815
142       2    2    4       68.0                  0.1496
143       2    2    4       64.5                  0.1419
144       2    2    4       62.5                  0.1375
145       2    2    4       61.5                  0.1353
146       2    3    4       53.5                  0.1177
147       2    3    4       61.0                  0.1342
148       2    3    4       62.5                  0.1375
149       2    3    4       75.5                  0.1661
150       2    3    4       80.5                  0.1771
151       1    1    5       69.5                  0.1529
152       1    1    5       87.5                  0.1925
153       1    1    5       80.5                  0.1771
154       1    1    5       83.0                  0.1826
155       1    1    5       83.0                  0.1826
156       1    2    5       80.0                  0.1760
157       1    2    5       71.5                  0.1573
158       1    2    5       71.5                  0.1573
159       1    2    5       80.0                  0.1760
160       1    2    5       79.5                  0.1749
161       1    3    5       61.0                  0.1342
162       1    3    5       81.5                  0.1793
163       1    3    5       71.0                  0.1562
164       1    3    5       71.0                  0.1562
165       1    3    5       70.0                  0.1540
166       2    1    5       81.5                  0.1793
167       2    1    5       83.5                  0.1837
168       2    1    5       73.5                  0.1617
169       2    1    5       61.5                  0.1353
170       2    1    5       87.5                  0.1925
171       2    2    5       80.5                  0.1771
172       2    2    5       65.0                  0.1430
173       2    2    5       59.5                  0.1309
174       2    2    5       60.0                  0.1320
175       2    2    5       60.0                  0.1320
176       2    3    5       52.0                  0.1144
177       2    3    5       59.0                  0.1298
178       2    3    5       61.5                  0.1353
179       2    3    5       75.0                  0.1650
180       2    3    5       79.0                  0.1738
181       1    1    6       72.0                  0.1584
182       1    1    6       92.5                  0.2035
183       1    1    6       84.0                  0.1848
184       1    1    6       88.0                  0.1936
185       1    1    6       87.5                  0.1925
186       1    2    6       82.0                  0.1804
187       1    2    6       74.0                  0.1628
188       1    2    6       74.0                  0.1628
189       1    2    6       83.0                  0.1826
190       1    2    6       81.0                  0.1782
191       1    3    6       63.0                  0.1386
192       1    3    6       82.5                  0.1815
193       1    3    6       75.0                  0.1650
194       1    3    6       72.0                  0.1584
195       1    3    6       75.0                  0.1650
196       2    1    6       85.5                  0.1881
197       2    1    6       89.5                  0.1969
198       2    1    6       79.5                  0.1749
199       2    1    6       63.0                  0.1386
200       2    1    6       94.5                  0.2079
201       2    2    6       85.5                  0.1881
202       2    2    6       68.5                  0.1507
203       2    2    6       60.5                  0.1331
204       2    2    6       65.5                  0.1441
205       2    2    6       62.0                  0.1364
206       2    3    6       54.5                  0.1199
207       2    3    6       61.0                  0.1342
208       2    3    6       62.0                  0.1364
209       2    3    6       80.0                  0.1760
210       2    3    6       79.0                  0.1738
211       1    1    7       77.5                  0.1705
212       1    1    7       98.5                  0.2167
213       1    1    7       88.5                  0.1947
214       1    1    7       92.5                  0.2035
215       1    1    7       92.0                  0.2024
216       1    2    7       85.0                  0.1870
217       1    2    7       77.5                  0.1705
218       1    2    7       77.5                  0.1705
219       1    2    7       85.0                  0.1870
220       1    2    7       82.0                  0.1804
221       1    3    7       67.5                  0.1485
222       1    3    7       83.5                  0.1837
223       1    3    7       81.0                  0.1782
224       1    3    7       72.5                  0.1595
225       1    3    7       76.5                  0.1683
226       2    1    7       93.5                  0.2057
227       2    1    7       94.5                  0.2079
228       2    1    7       85.0                  0.1870
229       2    1    7       64.5                  0.1419
230       2    1    7       99.5                  0.2189
231       2    2    7       90.0                  0.1980
232       2    2    7       72.0                  0.1584
233       2    2    7       62.0                  0.1364
234       2    2    7       70.0                  0.1540
235       2    2    7       63.0                  0.1386
236       2    3    7       57.5                  0.1265
237       2    3    7       62.5                  0.1375
238       2    3    7       62.5                  0.1375
239       2    3    7       83.5                  0.1837
240       2    3    7       80.0                  0.1760
data2 %>%
  group_by (LiveWeigth, Ewetype, Diet)%>%
  summarise(
    MeanWeekly = mean(LiveWeigth, na.rm = TRUE)
  )
`summarise()` has grouped output by 'LiveWeigth', 'Ewetype'. You can override
using the `.groups` argument.
# A tibble: 152 x 4
# Groups:   LiveWeigth, Ewetype [111]
   LiveWeigth Ewetype Diet  MeanWeekly
        <dbl> <fct>   <fct>      <dbl>
 1       52   2       3           52  
 2       53.5 2       3           53.5
 3       54.5 2       3           54.5
 4       55   2       3           55  
 5       55.5 2       3           55.5
 6       57.5 2       3           57.5
 7       59   2       3           59  
 8       59.5 2       1           59.5
 9       59.5 2       2           59.5
10       60   2       2           60  
# i 142 more rows
#Part E
data2 %>%
  group_by(LiveWeigth, Week, Diet) %>%
  summarise(
    MeanWeigth = mean(LiveWeigth, na.rm = TRUE),
    SDWeight = sd(LiveWeigth, na.rm = TRUE),
    Count = n()
  )
`summarise()` has grouped output by 'LiveWeigth', 'Week'. You can override
using the `.groups` argument.
# A tibble: 222 x 6
# Groups:   LiveWeigth, Week [199]
   LiveWeigth Week  Diet  MeanWeigth SDWeight Count
        <dbl> <chr> <fct>      <dbl>    <dbl> <int>
 1       52   5     3           52         NA     1
 2       53.5 4     3           53.5       NA     1
 3       54.5 1     3           54.5       NA     1
 4       54.5 3     3           54.5       NA     1
 5       54.5 6     3           54.5       NA     1
 6       55   2     3           55         NA     1
 7       55.5 0     3           55.5       NA     1
 8       57.5 7     3           57.5       NA     1
 9       59   5     3           59         NA     1
10       59.5 0     1           59.5       NA     1
# i 212 more rows
sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] car_3.1-2       carData_3.0-4   lubridate_1.9.2 forcats_1.0.0  
 [5] stringr_1.5.0   dplyr_1.1.2     purrr_1.0.1     readr_2.1.4    
 [9] tidyr_1.3.0     tibble_3.2.1    ggplot2_3.4.2   tidyverse_2.0.0

loaded via a namespace (and not attached):
 [1] compiler_4.1.2    pillar_1.9.0      tools_4.1.2       digest_0.6.29    
 [5] timechange_0.2.0  jsonlite_1.8.4    evaluate_0.14     lifecycle_1.0.3  
 [9] gtable_0.3.0      pkgconfig_2.0.3   rlang_1.1.0       cli_3.6.1        
[13] rstudioapi_0.15.0 yaml_2.2.1        xfun_0.29         fastmap_1.1.0    
[17] withr_2.5.0       knitr_1.37        hms_1.1.3         generics_0.1.1   
[21] vctrs_0.6.1       htmlwidgets_1.5.4 grid_4.1.2        tidyselect_1.2.0 
[25] glue_1.6.2        R6_2.5.1          fansi_0.5.0       rmarkdown_2.11   
[29] tzdb_0.2.0        magrittr_2.0.3    scales_1.2.1      htmltools_0.5.2  
[33] abind_1.4-5       colorspace_2.0-2  utf8_1.2.2        stringi_1.7.6    
[37] munsell_0.5.0

The echo: false option disables the printing of code (only output is displayed).