library(psych) # for the describe() command
library(expss) # for the cross_cases() command
## Loading required package: maditr
##
## To aggregate several columns with one summary: take(mtcars, mpg, hp, fun = mean, by = am)
d2 <- read.csv(file="Data/mydata.csv", header = T)
table(d2$gender) #table command shows what the levels of variable are and how many participants in each level
##
## f m nb
## 2258 774 52
table(d2$income)
##
## 1 low 2 middle 3 high rather not say
## 864 861 523 836
hist(d2$moa_role) #the hist command creates histogram of variable
hist(d2$idea)
hist(d2$efficacy)
hist(d2$stress)
We analyzed the skew and kurtosis of our continuous variable and most were within the accepted range (-2/+2). However, one variable (idea) was outside of the accepted range. For this analysis, we will use them anyway, but outside of this class this is bad practice.
describe(d2) #use this to check uni. normality...skew and kurtosis, (-2/+2)
## vars n mean sd median trimmed mad min max range skew kurtosis
## gender* 1 3084 1.28 0.49 1.00 1.21 0.00 1.0 3.0 2.0 1.38 0.84
## income* 2 3084 2.43 1.16 2.00 2.41 1.48 1.0 4.0 3.0 0.15 -1.44
## moa_role 3 3084 2.97 0.72 3.00 3.00 0.74 1.0 4.0 3.0 -0.33 -0.84
## idea 4 3084 3.58 0.38 3.62 3.62 0.37 1.0 4.0 3.0 -1.54 4.47
## efficacy 5 3084 3.13 0.45 3.10 3.13 0.44 1.1 4.0 2.9 -0.25 0.46
## stress 6 3084 3.05 0.60 3.00 3.05 0.59 1.3 4.7 3.4 0.04 -0.17
## se
## gender* 0.01
## income* 0.02
## moa_role 0.01
## idea 0.01
## efficacy 0.01
## stress 0.01
cross_cases(d2, gender, income)
|  income | ||||
|---|---|---|---|---|
|  1 low |  2 middle |  3 high |  rather not say | |
|  gender | ||||
|    f | 635 | 648 | 364 | 611 |
|    m | 212 | 202 | 155 | 205 |
|    nb | 17 | 11 | 4 | 20 |
|    #Total cases | 864 | 861 | 523 | 836 |
plot(d2$efficacy, d2$stress,
main="Scatterplot of efficacy and stress",
xlab = "efficacy",
ylab = "stress")
plot(d2$idea, d2$moa_role,
main="Scatterplot of idea and moa_role",
xlab = "idea",
ylab = "moa_role")
boxplot(data=d2, stress~income,
main="Boxplot of income and stress",
xlab = "income",
ylab = "stress")
boxplot(data=d2, stress~gender,
main="Boxplot of gender and stress",
xlab = "gender",
ylab = "stress")