setwd("C:/Users/lgawarec/Documents/MATH-650/R files")
getwd()
## [1] "C:/Users/lgawarec/Documents/MATH-650/R files"
# install.packages("readxl")
library(readxl)
Autoxlsx <- read_excel("~/MATH-650/Autoxlsx.xlsx")
View(Autoxlsx)
fix(Autoxlsx)
str(Autoxlsx)
## 'data.frame': 397 obs. of 9 variables:
## $ mpg : num 18 15 18 16 17 15 14 14 14 15 ...
## $ cylinders : num 8 8 8 8 8 8 8 8 8 8 ...
## $ displacement: num 307 350 318 304 302 429 454 440 455 390 ...
## $ horsepower : chr "130" "165" "150" "150" ...
## $ weight : num 3504 3693 3436 3433 3449 ...
## $ acceleration: num 12 11.5 11 12 10.5 10 9 8.5 10 8.5 ...
## $ year : num 70 70 70 70 70 70 70 70 70 70 ...
## $ origin : num 1 1 1 1 1 1 1 1 1 1 ...
## $ name : chr "chevrolet chevelle malibu" "buick skylark 320" "plymouth satellite" "amc rebel sst" ...
head(Autoxlsx)
## mpg cylinders displacement horsepower weight acceleration year origin
## 1 18 8 307 130 3504 12.0 70 1
## 2 15 8 350 165 3693 11.5 70 1
## 3 18 8 318 150 3436 11.0 70 1
## 4 16 8 304 150 3433 12.0 70 1
## 5 17 8 302 140 3449 10.5 70 1
## 6 15 8 429 198 4341 10.0 70 1
## name
## 1 chevrolet chevelle malibu
## 2 buick skylark 320
## 3 plymouth satellite
## 4 amc rebel sst
## 5 ford torino
## 6 ford galaxie 500
summary(Autoxlsx)
## mpg cylinders displacement horsepower
## Min. : 9.00 Min. :3.000 Min. : 68.0 Length:397
## 1st Qu.:17.50 1st Qu.:4.000 1st Qu.:104.0 Class :character
## Median :23.00 Median :4.000 Median :146.0 Mode :character
## Mean :23.52 Mean :5.458 Mean :193.5
## 3rd Qu.:29.00 3rd Qu.:8.000 3rd Qu.:262.0
## Max. :46.60 Max. :8.000 Max. :455.0
## weight acceleration year origin
## Min. :1613 Min. : 8.00 Min. :70.00 Min. :1.000
## 1st Qu.:2223 1st Qu.:13.80 1st Qu.:73.00 1st Qu.:1.000
## Median :2800 Median :15.50 Median :76.00 Median :1.000
## Mean :2970 Mean :15.56 Mean :75.99 Mean :1.574
## 3rd Qu.:3609 3rd Qu.:17.10 3rd Qu.:79.00 3rd Qu.:2.000
## Max. :5140 Max. :24.80 Max. :82.00 Max. :3.000
## name
## Length:397
## Class :character
## Mode :character
##
##
##
Autoxlsx$mpg
## [1] 18.0 15.0 18.0 16.0 17.0 15.0 14.0 14.0 14.0 15.0 15.0 14.0 15.0 14.0 24.0
## [16] 22.0 18.0 21.0 27.0 26.0 25.0 24.0 25.0 26.0 21.0 10.0 10.0 11.0 9.0 27.0
## [31] 28.0 25.0 25.0 19.0 16.0 17.0 19.0 18.0 14.0 14.0 14.0 14.0 12.0 13.0 13.0
## [46] 18.0 22.0 19.0 18.0 23.0 28.0 30.0 30.0 31.0 35.0 27.0 26.0 24.0 25.0 23.0
## [61] 20.0 21.0 13.0 14.0 15.0 14.0 17.0 11.0 13.0 12.0 13.0 19.0 15.0 13.0 13.0
## [76] 14.0 18.0 22.0 21.0 26.0 22.0 28.0 23.0 28.0 27.0 13.0 14.0 13.0 14.0 15.0
## [91] 12.0 13.0 13.0 14.0 13.0 12.0 13.0 18.0 16.0 18.0 18.0 23.0 26.0 11.0 12.0
## [106] 13.0 12.0 18.0 20.0 21.0 22.0 18.0 19.0 21.0 26.0 15.0 16.0 29.0 24.0 20.0
## [121] 19.0 15.0 24.0 20.0 11.0 20.0 21.0 19.0 15.0 31.0 26.0 32.0 25.0 16.0 16.0
## [136] 18.0 16.0 13.0 14.0 14.0 14.0 29.0 26.0 26.0 31.0 32.0 28.0 24.0 26.0 24.0
## [151] 26.0 31.0 19.0 18.0 15.0 15.0 16.0 15.0 16.0 14.0 17.0 16.0 15.0 18.0 21.0
## [166] 20.0 13.0 29.0 23.0 20.0 23.0 24.0 25.0 24.0 18.0 29.0 19.0 23.0 23.0 22.0
## [181] 25.0 33.0 28.0 25.0 25.0 26.0 27.0 17.5 16.0 15.5 14.5 22.0 22.0 24.0 22.5
## [196] 29.0 24.5 29.0 33.0 20.0 18.0 18.5 17.5 29.5 32.0 28.0 26.5 20.0 13.0 19.0
## [211] 19.0 16.5 16.5 13.0 13.0 13.0 31.5 30.0 36.0 25.5 33.5 17.5 17.0 15.5 15.0
## [226] 17.5 20.5 19.0 18.5 16.0 15.5 15.5 16.0 29.0 24.5 26.0 25.5 30.5 33.5 30.0
## [241] 30.5 22.0 21.5 21.5 43.1 36.1 32.8 39.4 36.1 19.9 19.4 20.2 19.2 20.5 20.2
## [256] 25.1 20.5 19.4 20.6 20.8 18.6 18.1 19.2 17.7 18.1 17.5 30.0 27.5 27.2 30.9
## [271] 21.1 23.2 23.8 23.9 20.3 17.0 21.6 16.2 31.5 29.5 21.5 19.8 22.3 20.2 20.6
## [286] 17.0 17.6 16.5 18.2 16.9 15.5 19.2 18.5 31.9 34.1 35.7 27.4 25.4 23.0 27.2
## [301] 23.9 34.2 34.5 31.8 37.3 28.4 28.8 26.8 33.5 41.5 38.1 32.1 37.2 28.0 26.4
## [316] 24.3 19.1 34.3 29.8 31.3 37.0 32.2 46.6 27.9 40.8 44.3 43.4 36.4 30.0 44.6
## [331] 40.9 33.8 29.8 32.7 23.7 35.0 23.6 32.4 27.2 26.6 25.8 23.5 30.0 39.1 39.0
## [346] 35.1 32.3 37.0 37.7 34.1 34.7 34.4 29.9 33.0 34.5 33.7 32.4 32.9 31.6 28.1
## [361] 30.7 25.4 24.2 22.4 26.6 20.2 17.6 28.0 27.0 34.0 31.0 29.0 27.0 24.0 36.0
## [376] 37.0 31.0 38.0 36.0 36.0 36.0 34.0 38.0 32.0 38.0 25.0 38.0 26.0 22.0 32.0
## [391] 36.0 27.0 27.0 44.0 32.0 28.0 31.0
head(Autoxlsx$mpg)
## [1] 18 15 18 16 17 15
mean(Autoxlsx$mpg)
## [1] 23.51587
vmpg=var(Autoxlsx$mpg)
sqrt(vmpg)
## [1] 7.825804
hist(Autoxlsx$mpg)
boxplot(Autoxlsx$mpg)
