On this RMarkdown I’ll present the results of the assignment 4

First, lets mark the package readr.

library(readr)

Now we have to import the data

View(attitude)

Then let’s view a summary through the function “describe”, but first, activate psych package.

library(psych)
describe(attitude)
##            vars  n  mean    sd median trimmed   mad min max range  skew
## rating        1 30 64.63 12.17   65.5   65.21 10.38  40  85    45 -0.36
## complaints    2 30 66.60 13.31   65.0   67.08 14.83  37  90    53 -0.22
## privileges    3 30 53.13 12.24   51.5   52.75 10.38  30  83    53  0.38
## learning      4 30 56.37 11.74   56.5   56.58 14.83  34  75    41 -0.05
## raises        5 30 64.63 10.40   63.5   64.50 11.12  43  88    45  0.20
## critical      6 30 74.77  9.89   77.5   75.83  7.41  49  92    43 -0.87
## advance       7 30 42.93 10.29   41.0   41.83  8.90  25  72    47  0.85
##            kurtosis   se
## rating        -0.77 2.22
## complaints    -0.68 2.43
## privileges    -0.41 2.23
## learning      -1.22 2.14
## raises        -0.60 1.90
## critical       0.17 1.81
## advance        0.47 1.88
  1. MEAN
mean(attitude$rating)
## [1] 64.63333
mean(attitude$complaints)
## [1] 66.6
mean(attitude$privileges)
## [1] 53.13333
mean(attitude$learning)
## [1] 56.36667
mean(attitude$raises)
## [1] 64.63333
mean(attitude$critical)
## [1] 74.76667
mean(attitude$advance)
## [1] 42.93333
  1. MEDIAN
median(attitude$rating)
## [1] 65.5
median(attitude$complaints)
## [1] 65
median(attitude$privileges)
## [1] 51.5
median(attitude$learning)
## [1] 56.5
median(attitude$raises)
## [1] 63.5
median(attitude$critical)
## [1] 77.5
median(attitude$advance)
## [1] 41
  1. MODE

First result: Value

Second result: Frequency

Rating

moda_rating<-names(sort(-table(attitude$rating)))[1]
freq_moda<-table(attitude$rating)[moda_rating]
print(freq_moda)
## 43 
##  2

Complaints

moda_complaints<-names(sort(-table(attitude$complaints)))[1]
freq_moda<-table(attitude$complaints)[moda_complaints]
print(freq_moda)
## 60 
##  2

Privileges

moda_privileges<-names(sort(-table(attitude$privileges)))[1]
freq_moda<-table(attitude$privileges)[moda_privileges]
print(freq_moda)
## 42 
##  3

Learnings

moda_learning<-names(sort(-table(attitude$learning)))[1]
freq_moda<-table(attitude$learning)[moda_learning]
print(freq_moda)
## 39 
##  2

Raises

moda_raises<-names(sort(-table(attitude$raises)))[1]
freq_moda<-table(attitude$raises)[moda_raises]
print(freq_moda)
## 66 
##  3

Critical

moda_critical<-names(sort(-table(attitude$critical)))[1]
freq_moda<-table(attitude$critical)[moda_critical]
print(freq_moda)
## 80 
##  4

Advance

moda_advance<-names(sort(-table(attitude$advance)))[1]
freq_moda<-table(attitude$advance)[moda_advance]
print(freq_moda)
## 41 
##  4
  1. MAX
max(attitude$rating)
## [1] 85
max(attitude$complaints)
## [1] 90
max(attitude$privileges)
## [1] 83
max(attitude$learning)
## [1] 75
max(attitude$raises)
## [1] 88
max(attitude$critical)
## [1] 92
max(attitude$advance)
## [1] 72

5)MIN

min(attitude$rating)
## [1] 40
min(attitude$complaints)
## [1] 37
min(attitude$privileges)
## [1] 30
min(attitude$learning)
## [1] 34
min(attitude$raises)
## [1] 43
min(attitude$critical)
## [1] 49
min(attitude$advance)
## [1] 25

6)RANGE

range(attitude$rating)
## [1] 40 85
range(attitude$complaints)
## [1] 37 90
range(attitude$privileges)
## [1] 30 83
range(attitude$learning)
## [1] 34 75
range(attitude$raises)
## [1] 43 88
range(attitude$critical)
## [1] 49 92
range(attitude$advance)
## [1] 25 72

7)QUANTILE

quantile(attitude$rating)
##    0%   25%   50%   75%  100% 
## 40.00 58.75 65.50 71.75 85.00
quantile(attitude$complaints)
##   0%  25%  50%  75% 100% 
## 37.0 58.5 65.0 77.0 90.0
quantile(attitude$privileges)
##   0%  25%  50%  75% 100% 
## 30.0 45.0 51.5 62.5 83.0
quantile(attitude$learning)
##    0%   25%   50%   75%  100% 
## 34.00 47.00 56.50 66.75 75.00
quantile(attitude$raises)
##    0%   25%   50%   75%  100% 
## 43.00 58.25 63.50 71.00 88.00
quantile(attitude$critical)
##    0%   25%   50%   75%  100% 
## 49.00 69.25 77.50 80.00 92.00
quantile(attitude$advance)
##    0%   25%   50%   75%  100% 
## 25.00 35.00 41.00 47.75 72.00

8)IQR

IQR(attitude$rating)
## [1] 13
IQR(attitude$complaints)
## [1] 18.5
IQR(attitude$privileges)
## [1] 17.5
IQR(attitude$learning)
## [1] 19.75
IQR(attitude$raises)
## [1] 12.75
IQR(attitude$critical)
## [1] 10.75
IQR(attitude$advance)
## [1] 12.75

9)VARIANCE

var(attitude$rating)
## [1] 148.1713
var(attitude$complaints)
## [1] 177.2828
var(attitude$privileges)
## [1] 149.7057
var(attitude$learning)
## [1] 137.7575
var(attitude$raises)
## [1] 108.1023
var(attitude$critical)
## [1] 97.9092
var(attitude$advance)
## [1] 105.8575

10)STANDAR DESVIATION

sd(attitude$rating)
## [1] 12.17256
sd(attitude$complaints)
## [1] 13.31476
sd(attitude$privileges)
## [1] 12.23543
sd(attitude$learning)
## [1] 11.73701
sd(attitude$raises)
## [1] 10.39723
sd(attitude$critical)
## [1] 9.894908
sd(attitude$advance)
## [1] 10.28871

11)CORRELATION

cor(attitude)
##               rating complaints privileges  learning    raises  critical
## rating     1.0000000  0.8254176  0.4261169 0.6236782 0.5901390 0.1564392
## complaints 0.8254176  1.0000000  0.5582882 0.5967358 0.6691975 0.1877143
## privileges 0.4261169  0.5582882  1.0000000 0.4933310 0.4454779 0.1472331
## learning   0.6236782  0.5967358  0.4933310 1.0000000 0.6403144 0.1159652
## raises     0.5901390  0.6691975  0.4454779 0.6403144 1.0000000 0.3768830
## critical   0.1564392  0.1877143  0.1472331 0.1159652 0.3768830 1.0000000
## advance    0.1550863  0.2245796  0.3432934 0.5316198 0.5741862 0.2833432
##              advance
## rating     0.1550863
## complaints 0.2245796
## privileges 0.3432934
## learning   0.5316198
## raises     0.5741862
## critical   0.2833432
## advance    1.0000000

Let’s mark the packages for RMarkdown

library(latexpdf)

Thanks David Espinoza