Qualtrics data

First, you’ll want to read in your data and remove unnecessary columns and rows. You can download a copy of the data here

library(dplyr)
library(ggplot2)

## Read in qualtrics data as csv
dat <- read.csv("qualtrics_data.csv")

## Keep only those variables I created
dat <- select(dat, sex, degree, grocery_1, boba)

## Remove first two rows with metadata
dat <- dat[3:nrow(dat), ]

Also don’t forget – numeric characters will be exported as characters because of the character strings that were included in the first two rows. You may run into errors if this is not changed

## Error
t.test(grocery_1 ~ degree, dat)

## Error in if (stderr < 10 * .Machine$double.eps * max(abs(mx), abs(my))) stop("data are essentially constant"): missing value where TRUE/FALSE needed

The error will go away if you convert with as.numeric()

## Change numeric vectors into numeric
dat <- mutate(dat, grocery_1 = as.numeric(grocery_1))

## Do your statistics!
t.test(grocery_1 ~ degree, dat)

## 
##  Welch Two Sample t-test
## 
## data:  grocery_1 by degree
## t = -2.61, df = 39.8, p-value = 0.013
## alternative hypothesis: true difference in means between group Humanities and group STEM is not equal to 0
## 95 percent confidence interval:
##  -18.5721  -2.3612
## sample estimates:
## mean in group Humanities       mean in group STEM 
##                   17.933                   28.400