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 drop variable use NULL: let(mtcars, am = NULL) %>% head()
## 
## Attaching package: 'maditr'
## The following object is masked from 'package:base':
## 
##     sort_by

Import Data

# import our data for the lab

d2 <- read.csv(file ="Data/mydata.csv" , header = T)

Univariate Plots: Histograms & Tables

table(d2$gender) #the table command shows us what the levels of this variable are and how many participants are in each level. replace these two variablenumber texts with categorical variables
## 
##    f    m   nb 
## 2252  770   53
table(d2$marriage5)
## 
##             are currently divorced from one another 
##                                                 712 
##                are currently married to one another 
##                                                2084 
##       never married each other and are not together 
##                                                 235 
## never married each other but are currently together 
##                                                  44
hist(d2$moa_role) # hist command creates the histogram for the variables, continuous variables

hist(d2$moa_maturity)

hist(d2$swb)

hist(d2$belong)

Univariate Normality

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

We analyzed the skew and kurtosis of our … and most were within the accepted range (-2/+2). However, some variables (list them in parentheses) were outside of the accepted range. For this analysis, we will use them anyway, but outside of this class this is bad practice.

describe(d2) #used to check univariate normality, skew and kurtosis range is (-2/+2)
##              vars    n mean   sd median trimmed  mad min max range  skew
## gender*         1 3075 1.28 0.49   1.00    1.21 0.00 1.0   3   2.0  1.39
## marriage5*      2 3075 1.87 0.59   2.00    1.84 0.00 1.0   4   3.0  0.45
## moa_role        3 3075 2.97 0.72   3.00    3.00 0.74 1.0   4   3.0 -0.33
## moa_maturity    4 3075 3.59 0.43   3.67    3.65 0.49 1.0   4   3.0 -1.20
## swb             5 3075 4.47 1.32   4.67    4.53 1.48 1.0   7   6.0 -0.37
## belong          6 3075 3.23 0.61   3.30    3.25 0.59 1.3   5   3.7 -0.27
##              kurtosis   se
## gender*          0.87 0.01
## marriage5*       1.51 0.01
## moa_role        -0.85 0.01
## moa_maturity     1.89 0.01
## swb             -0.45 0.02
## belong          -0.13 0.01

Bivariate Plots

Crosstabs

cross_cases(d2, gender, marriage5) #update variables with categorical variables and next the continuous Vs
 marriage5 
 are currently divorced from one another   are currently married to one another   never married each other and are not together   never married each other but are currently together 
 gender 
   f  529 1518 173 32
   m  170 532 56 12
   nb  13 34 6
   #Total cases  712 2084 235 44

Scatterplots

plot(d2$moa_role, d2$moa_maturity,
     main="Scatterplot of moa_role and moa_maturity",
     xlab = "moa_role",
     ylab = "moa_maturity")

plot(d2$swb, d2$belong,
     main="Scatterplot of swb and belong",
     xlab = "swb",
     ylab = "belong")

plot(d2$swb, d2$moa_maturity,
     main="Scatterplot of swb and moa_maturity",
     xlab = "swb",
     ylab = "moa_maturity")

plot(d2$moa_role, d2$swb,
     main="Scatterplot of moa_role and swb",
     xlab = "moa_role",
     ylab = "swb")

plot(d2$moa_role, d2$belong,
     main="Scatterplot of moa_role and belong",
     xlab = "moa_role",
     ylab = "belong")

plot(d2$moa_maturity, d2$belong,
     main="Scatterplot of moa_maturity and belong",
     xlab = "moa_maturity",
     ylab = "belong")

Boxplots

# boxplots use 1 categorical and 1 continuous variable
# use them in the right order! continuous~categorical

boxplot(data=d2, moa_role~gender,
        main="Boxplot of gender and moa_role",
        xlab = "gender",
        ylab = "moa_role")

boxplot(data=d2, moa_maturity~marriage5,
        main="Boxplot of marriage5 and moa_maturity",
        xlab = "marriage5",
        ylab = "moa_maturity")

boxplot(data=d2, moa_maturity~gender,
        main="Boxplot of gender and moa_maturity",
        xlab = "gender",
        ylab = "moa_maturity")

boxplot(data=d2, belong~gender,
        main="Boxplot of gender and belong",
        xlab = "gender",
        ylab = "belong")

boxplot(data=d2, belong~marriage5,
        main="Boxplot of marriage5 and belong",
        xlab = "marriage5",
        ylab = "belong")

boxplot(data=d2, swb~marriage5,
        main="Boxplot of marriage5 and swb",
        xlab = "marriage5",
        ylab = "swb")

boxplot(data=d2, swb~gender,
        main="Boxplot of gender and swb",
        xlab = "gender",
        ylab = "swb")