## Rows: 70 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): HANDICAP
## dbl (1): SCORE
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Problem 1
## Code for Question 3
mean(Handicap$SCORE)
## [1] 4.928571
## Variance
sd(Handicap$SCORE)
## [1] 1.718792
## Code for Question 4
attach(Handicap)
## Finds mean by Handicap type
mean(SCORE ~ HANDICAP)
## AMPUTEE CRUTCHES HEARING NONE WHEELCHAIR
## 4.428571 5.921429 4.050000 4.900000 5.342857
## Variance of means by Handicap
sd(mean(SCORE ~ HANDICAP))
## [1] 0.7382584
## Variance of groups by Handicap
sd(SCORE ~ HANDICAP)
## AMPUTEE CRUTCHES HEARING NONE WHEELCHAIR
## 1.585719 1.481776 1.532595 1.793578 1.748280
## Mean of Variance
mean(sd(SCORE ~ HANDICAP))
## [1] 1.62839
## Code for Question 5
dox_aov(SCORE ~ HANDICAP, Handicap)
ANOVA Summary
|
|
Df
|
Sum Sq
|
Mean Sq
|
F value
|
Pr(>F)
|
|
HANDICAP
|
4
|
30.52
|
7.630
|
2.862
|
0.03013
|
|
Residuals
|
65
|
173.32
|
2.666
|
NA
|
NA
|
|
Total
|
69
|
203.84
|
NA
|
NA
|
NA
|
dox_boxplot(SCORE ~ HANDICAP, Handicap)
## Question 7
x <- rf(10000, 4, 65)
hist(x)
abline(v=2.862)
## Question 8
dox_resid(SCORE ~ HANDICAP, Handicap)
Problem 2
## New names:
## Rows: 46 Columns: 8
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (1): Judge dbl (1): Percent lgl (6): ...3, ...4, ...5, ...6, ...7, ...8
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...3`
## • `` -> `...4`
## • `` -> `...5`
## • `` -> `...6`
## • `` -> `...7`
## • `` -> `...8`
## Boxplot
dox_boxplot(Percent ~ Judge, spock)
## ANOVA
dox_aov(Percent ~ Judge, spock)
## # A tibble: 7 × 2
## Judge n
## <chr> <int>
## 1 A 5
## 2 B 6
## 3 C 8
## 4 D 2
## 5 E 7
## 6 F 9
## 7 Spock 9
ANOVA Summary
|
|
Df
|
Sum Sq
|
Mean Sq
|
F value
|
Pr(>F)
|
|
Judge
|
6
|
1850
|
308.3
|
6.279
|
0.0001108
|
|
Residuals
|
39
|
1915
|
49.1
|
NA
|
NA
|
|
Total
|
45
|
3764
|
NA
|
NA
|
NA
|
Problem 3
## Rows: 36 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Building, Location
## dbl (1): Count
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## W/o Log count
dox_aov(Count ~ Building + Location, HW13Bacteria)
ANOVA Summary
|
|
Df
|
Sum Sq
|
Mean Sq
|
F value
|
Pr(>F)
|
|
Building
|
5
|
3845562
|
769112
|
7.3797
|
0.0001602
|
|
Location
|
2
|
206372
|
103186
|
0.9901
|
0.3841829
|
|
Residuals
|
28
|
2918163
|
104220
|
NA
|
NA
|
|
Total
|
35
|
6970097
|
NA
|
NA
|
NA
|
dox_boxplot(Count ~ Building + Location, HW13Bacteria)
dox_resid(Count ~ Building + Location, HW13Bacteria)
## mutation for log
df1 <- mutate(HW13Bacteria, logcount = log(Count))
## W/ logcount
dox_aov(logcount ~ Building + Location, df1)
ANOVA Summary
|
|
Df
|
Sum Sq
|
Mean Sq
|
F value
|
Pr(>F)
|
|
Building
|
5
|
36.181
|
7.236
|
6.087
|
0.0006198
|
|
Location
|
2
|
3.016
|
1.508
|
1.268
|
0.2969377
|
|
Residuals
|
28
|
33.287
|
1.189
|
NA
|
NA
|
|
Total
|
35
|
72.484
|
NA
|
NA
|
NA
|
dox_boxplot(logcount ~ Building + Location, df1)
dox_resid(logcount ~ Building + Location, df1)
