# remember, you might need to install packages
library(psych) # for the describe() command
library(expss) # for the cross_cases() command
Basic Statistics HW
Load Libraries
Load Data
<- read.csv(file="Data/mydata.csv", header=T)
d names(d)
[1] "sexual_orientation" "mhealth" "support"
[4] "swemws" "rse" "iou"
Univariate Plots: Histograms & Tables
table(d$mhealth)
anxiety disorder bipolar
117 5
depression eating disorders
29 29
none or NA obsessive compulsive disorder
883 22
other ptsd
34 21
table(d$sexual_orientation)
Asexual Bi Gay/Lesbian
31 144 49
Heterosexual/Straight I use another term Prefer not to say
805 34 77
hist(d$support)
hist(d$swemws)
hist(d$rse)
hist(d$iou)
Univariate Normality
Check skew and kurtosis.
describe(d)
vars n mean sd median trimmed mad min max range skew
sexual_orientation* 1 1140 3.79 1.02 4.00 3.81 0.00 1 6 5 -0.50
mhealth* 2 1140 4.63 1.41 5.00 4.88 0.00 1 8 7 -1.41
support 3 1140 3.57 0.96 3.67 3.62 0.99 1 5 4 -0.43
swemws 4 1140 3.14 0.85 3.14 3.17 0.85 1 5 4 -0.26
rse 5 1140 2.63 0.72 2.70 2.65 0.74 1 4 3 -0.24
iou 6 1140 2.56 0.91 2.41 2.50 0.99 1 5 4 0.51
kurtosis se
sexual_orientation* 1.21 0.03
mhealth* 2.52 0.04
support -0.57 0.03
swemws -0.29 0.03
rse -0.74 0.02
iou -0.62 0.03
Bivariate Plots
Crosstabs
cross_cases(d, mhealth, sexual_orientation)
sexual_orientation | ||||||
---|---|---|---|---|---|---|
Asexual | Bi | Gay/Lesbian | Heterosexual/Straight | I use another term | Prefer not to say | |
mhealth | ||||||
anxiety disorder | 3 | 24 | 11 | 69 | 3 | 7 |
bipolar | 2 | 1 | 1 | 1 | ||
depression | 6 | 21 | 2 | |||
eating disorders | 9 | 1 | 15 | 1 | 3 | |
none or NA | 24 | 80 | 30 | 663 | 27 | 59 |
obsessive compulsive disorder | 2 | 4 | 2 | 13 | 1 | |
other | 2 | 13 | 3 | 10 | 6 | |
ptsd | 6 | 1 | 13 | 1 | ||
#Total cases | 31 | 144 | 49 | 805 | 34 | 77 |
Scatterplots
plot(d$support, d$swemws,
main="Scatterplot of Social Support and Mental Well-Being",
xlab = "Social Support",
ylab = "Mental Well-being")
plot(d$support, d$rse,
main="Scatterplot of Social Support and Self-Esteem",
xlab = "Social Support",
ylab = "Self-Esteem")
plot(d$support, d$iou,
main="Scatterplot of Social Support and Intolerance of Uncertainty",
xlab = "Social Support",
ylab = "Intolerance of Uncertainty")
plot(d$swemws, d$rse,
main="Scatterplot of Mental Well-Being and Self-Esteem",
xlab = "Mental Well-Being",
ylab = "Self-Esteem")
plot(d$swemws, d$iou,
main="Scatterplot of Mental Well-Being and Intolerance of Uncertainty",
xlab = "Mental Well-Being",
ylab = "Intolerance of Uncertainty")
plot(d$rse, d$iou,
main="Scatterplot of Self-Esteem and Intolerance of Uncertainty",
xlab = "Self-Esteem",
ylab = "Intolerance of Uncertainty")
Boxplots
# rememeber that continuous variable comes first, CONTINUOUS~CATEGORICAL
boxplot(data=d, support~sexual_orientation,
main="Boxplot of Social Support and Sexual Orientation",
xlab = "Sexual Orientation",
ylab = "Social Support")
boxplot(data=d, rse~mhealth,
main="Boxplot of Self-Esteem and Mental Health Diagnosis",
xlab = "Mental Health Diagnosis",
ylab = "Self-Esteem")
Write-Up
We reviewed plots and descriptive statistics for our six chosen variables. All four of our continuous variables had skew and kurtosis within the accepted range (-2/+2).