Introductory Data Analysis in R
Maria Spencer
September 6, 2015
The following is a basic analysis of mtcars, a data set preloaded in R.
Summary of the data
The command summary(mtcars) will summarize the data, detailing the mean, media and max & min values of each variable:
summary(mtcars)## mpg cyl disp hp
## Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0
## 1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5
## Median :19.20 Median :6.000 Median :196.3 Median :123.0
## Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7
## 3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0
## Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0
## drat wt qsec vs
## Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
## 1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
## Median :3.695 Median :3.325 Median :17.71 Median :0.0000
## Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
## 3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
## Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
## am gear carb
## Min. :0.0000 Min. :3.000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
## Median :0.0000 Median :4.000 Median :2.000
## Mean :0.4062 Mean :3.688 Mean :2.812
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :8.000Description of the Data
To calculate the standard deviation and other descriptions of the data, install the package ‘psych’ and then run the command describe(mtcars). The result will include information about the standard deviation as well as the skew and distribution of the data.
require(psych)## Loading required package: psychdescribe(mtcars) ## vars n mean sd median trimmed mad min max range skew
## mpg 1 32 20.09 6.03 19.20 19.70 5.41 10.40 33.90 23.50 0.61
## cyl 2 32 6.19 1.79 6.00 6.23 2.97 4.00 8.00 4.00 -0.17
## disp 3 32 230.72 123.94 196.30 222.52 140.48 71.10 472.00 400.90 0.38
## hp 4 32 146.69 68.56 123.00 141.19 77.10 52.00 335.00 283.00 0.73
## drat 5 32 3.60 0.53 3.70 3.58 0.70 2.76 4.93 2.17 0.27
## wt 6 32 3.22 0.98 3.33 3.15 0.77 1.51 5.42 3.91 0.42
## qsec 7 32 17.85 1.79 17.71 17.83 1.42 14.50 22.90 8.40 0.37
## vs 8 32 0.44 0.50 0.00 0.42 0.00 0.00 1.00 1.00 0.24
## am 9 32 0.41 0.50 0.00 0.38 0.00 0.00 1.00 1.00 0.36
## gear 10 32 3.69 0.74 4.00 3.62 1.48 3.00 5.00 2.00 0.53
## carb 11 32 2.81 1.62 2.00 2.65 1.48 1.00 8.00 7.00 1.05
## kurtosis se
## mpg -0.37 1.07
## cyl -1.76 0.32
## disp -1.21 21.91
## hp -0.14 12.12
## drat -0.71 0.09
## wt -0.02 0.17
## qsec 0.34 0.32
## vs -2.00 0.09
## am -1.92 0.09
## gear -1.07 0.13
## carb 1.26 0.29Creating Variables
Variables can be created and manipulated using R. Use the ‘<-’ symbol as an ‘equal to’ indicator.
x <- 2 * 2
y <- x + 10
z <- x / yArithmatic Functions with the Variables
Now that values have been assigned to the variables, they can be incorporated into functions which R will execute. R can also solve for varaibles with the command “solve()”
zz <-(x+1)*(y-1)
solve(x)## [,1]
## [1,] 0.25This analysis was powered by R:
Here is a “chunk” of R code with a comment in it:
100/10 #This math I could do in my head## [1] 10Here is R code with the code hidden, which is accomplished with the echo = FALSE command. The code is the round command applied to mtcars and taken to one digit.
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.9 2.6 16.5 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.9 2.9 17.0 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.8 2.3 18.6 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.1 3.2 19.4 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.1 3.4 17.0 0 0 3 2
## Valiant 18.1 6 225.0 105 2.8 3.5 20.2 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.2 3.6 15.8 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.7 3.2 20.0 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.9 3.1 22.9 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.9 3.4 18.3 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.9 3.4 18.9 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.1 4.1 17.4 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.1 3.7 17.6 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.1 3.8 18.0 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.9 5.2 18.0 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.0 5.4 17.8 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.2 5.3 17.4 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.1 2.2 19.5 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.9 1.6 18.5 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.2 1.8 19.9 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.7 2.5 20.0 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.8 3.5 16.9 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.1 3.4 17.3 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.7 3.8 15.4 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.1 3.8 17.1 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.1 1.9 18.9 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.4 2.1 16.7 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.8 1.5 16.9 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.2 3.2 14.5 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.6 2.8 15.5 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.5 3.6 14.6 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.1 2.8 18.6 1 1 4 2