# remember, you might need to install packages
library(psych) # for the describe() command
library(expss) # for the cross_cases() commandBasic Statistics Lab
Load Libraries
Load Data
# WILL NEED TO UPDATE THIS FOR THE HW!!! USE MYDATA
d <- read.csv(file="Data/labdata.csv", header=T)
names(d)[1] "pet" "mhealth" "iou" "rse" "phq" "pss" Univariate Plots: Histograms & Tables
table(d$pet)
bird cat cat and dog
5 211 136
dog fish multiple types of pet
246 35 104
no pets other
396 68 table(d$mhealth)
anxiety disorder bipolar
128 5
depression eating disorders
31 28
none or NA obsessive compulsive disorder
927 26
other ptsd
34 22 #
hist(d$iou)
hist(d$rse)
hist(d$phq)
hist(d$pss)
Univariate Normality
Check skew and kurtosis.
describe(d) vars n mean sd median trimmed mad min max range skew kurtosis
pet* 1 1201 4.94 2.05 5.00 4.99 2.97 1.00 8 7.00 -0.13 -1.49
mhealth* 2 1201 4.62 1.42 5.00 4.86 0.00 1.00 8 7.00 -1.41 2.38
iou 3 1201 2.57 0.90 2.41 2.51 0.99 1.04 5 3.96 0.51 -0.57
rse 4 1201 2.63 0.72 2.70 2.64 0.74 1.00 4 3.00 -0.21 -0.72
phq 5 1201 2.09 0.87 1.89 2.01 0.99 1.00 4 3.00 0.61 -0.74
pss 6 1201 2.95 0.95 3.00 2.94 1.11 1.00 5 4.00 0.07 -0.77
se
pet* 0.06
mhealth* 0.04
iou 0.03
rse 0.02
phq 0.02
pss 0.03Bivariate Plots
Crosstabs
cross_cases(d, pet, mhealth)| mhealth | ||||||||
|---|---|---|---|---|---|---|---|---|
| anxiety disorder | bipolar | depression | eating disorders | none or NA | obsessive compulsive disorder | other | ptsd | |
| pet | ||||||||
| bird | 1 | 1 | 3 | |||||
| cat | 29 | 1 | 4 | 3 | 164 | 4 | 3 | 3 |
| cat and dog | 19 | 1 | 6 | 99 | 4 | 5 | 2 | |
| dog | 32 | 3 | 12 | 6 | 176 | 4 | 5 | 8 |
| fish | 3 | 1 | 30 | 1 | ||||
| multiple types of pet | 12 | 3 | 3 | 76 | 2 | 4 | 4 | |
| no pets | 25 | 1 | 8 | 9 | 326 | 9 | 14 | 4 |
| other | 7 | 2 | 53 | 2 | 3 | 1 | ||
| #Total cases | 128 | 5 | 31 | 28 | 927 | 26 | 34 | 22 |
Scatterplots
plot(d$iou, d$rse,
main="Scatterplot of Intolerance of Uncertainty and Self-Esteem",
xlab = "Intolerance of Uncertainty",
ylab = "Self-Esteem")
plot(d$iou, d$phq,
main="Scatterplot of Intolerance of Uncertainty and Depression",
xlab = "Intolerance of Uncertainty",
ylab = "Depression")
plot(d$iou, d$pss,
main="Scatterplot of Intolerance of Uncertainty and Stress",
xlab = "Intolerance of Uncertainty",
ylab = "Stress")
plot(d$rse, d$phq,
main="Scatterplot of Self-Esteem and Depression",
xlab = "Self-Esteem",
ylab = "Depression")
plot(d$rse, d$pss,
main="Scatterplot of Self-Esteem and Stress",
xlab = "Self-Esteem",
ylab = "Stress")
plot(d$phq, d$pss,
main="Scatterplot of Depression and Stress",
xlab = "Depression",
ylab = "Stress")
Boxplots
# remember that continuous variale comes first, CONTINUOUS~CATEGORICAL
boxplot(data=d, iou~pet,
main="Boxplot of Intolerance of Uncertainty and Pet Type",
xlab = "Pet Type",
ylab = "Intolerance of Uncertainty")
boxplot(data=d, iou~mhealth,
main="Boxplot of Intolerance of Uncertainty and Mental Health Diagnosis",
xlab = "Mental Health Diagnosis",
ylab = "Intolerance of Uncertainty")
Write-Up
Once again, you need to create a write-up reviewing the most important things you did here. Again, it should be suitable for inclusion in a manuscript. Make sure you include your review of skewness and kurtosis. I have given you two potential templates you can follow below, depending upon your needs – you should delete the other text in this section and only include your write-up.
If skew and kurtosis are good: 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).
If skew and kurtosis have issues: We reviewed plots and descriptive statistics for our six chosen variables. [Placeholder] variables had issues with skew and/or kurtosis: worry scores were negatively skewed (-3.15) and self-esteem scores were kurtotic (2.50). The other [placeholder] variables had skew and kurtosis within the accepted range (-2/+2).