Basic Statistics

Load Libraries

# if you haven't run this code before, you'll need to download the below packages first
# instructions on how to do this are included in the video
# but as a reminder, you use the packages tab to the right

library(psych) # for the describe() command
library(expss) # for the cross_cases() command
## Loading required package: maditr
## 
## To get total summary skip 'by' argument: take_all(mtcars, mean)
## 
## Attaching package: 'maditr'
## The following object is masked from 'package:base':
## 
##     sort_by

import data

#import lab data
#import HW mydata.csv

d3 <- read.csv(file="Data/mydata.csv", header = T)

Univariate Plots: Histograms & Tables

table(d3$gender)
## 
##    f    m   nb 
## 1546  527   31
table(d3$age)
## 
## 1 between 18 and 25 2 between 26 and 35 3 between 36 and 45           4 over 45 
##                1937                 113                  37                  17
hist(d3$moa_independence) 

hist(d3$swb)

hist(d3$belong)

hist(d3$socmeduse)

Univariate Normality

I analyzed the skew and kurtosis of the continuous variables and all were within the accepted range (-2/+2).

describe(d3)
##                  vars    n  mean   sd median trimmed  mad  min max range  skew
## gender*             1 2104  1.28 0.48   1.00    1.21 0.00  1.0   3   2.0  1.37
## age*                2 2104  1.11 0.43   1.00    1.00 0.00  1.0   4   3.0  4.42
## moa_independence    3 2104  3.54 0.47   3.67    3.61 0.49  1.0   4   3.0 -1.49
## swb                 4 2104  4.43 1.33   4.50    4.49 1.48  1.0   7   6.0 -0.36
## belong              5 2104  3.21 0.61   3.20    3.23 0.59  1.3   5   3.7 -0.27
## socmeduse           6 2104 34.24 8.63  35.00   34.51 7.41 11.0  55  44.0 -0.30
##                  kurtosis   se
## gender*              0.76 0.01
## age*                21.13 0.01
## moa_independence     2.77 0.01
## swb                 -0.49 0.03
## belong              -0.12 0.01
## socmeduse            0.18 0.19

Bivariate Plots

Crosstabs

cross_cases(d3, gender, age)
 age 
 1 between 18 and 25   2 between 26 and 35   3 between 36 and 45   4 over 45 
 gender 
   f  1439 68 27 12
   m  468 45 9 5
   nb  30 1
   #Total cases  1937 113 37 17

Scatterplots

plot(d3$moa_independence, d3$swb,
     main="Scatterplot of moa_independence and swb",
     xlab = "moa_independence",
     ylab = "swb")

plot(d3$belong, d3$socmeduse,
     main="Scatterplot of belong and socmeduse",
     xlab = "belong",
     ylab = "socmeduse")

Boxplots

boxplot(data=d3, moa_independence~age,
        main="Boxplot of age and moa_independence",
        xlab = "age",
        ylab = "moa_independence")

boxplot(data=d3, belong~gender,
        main="Boxplot of gender and belong",
        xlab = "gender",
        ylab = "belong")