Learn T-tests

Load Packages

haven

# Check if haven is already installed and if it is, load it.
if (!require(haven))
  # If it's not intalled, then tell R to install it.
  install.packages("haven", dependencies = TRUE)

tidyverse

if (!require(tidyverse))
  install.packages("tidyverse", dependencies = TRUE)
  library(tidyverse)

Import Data

library(haven)
Harry_Potter_Data_5_ <- read_sav("Harry Potter Data (5).sav")
View(Harry_Potter_Data_5_)

T-test

t.test(formula = FFM_3 ~ CoinFlip,
       data = Harry_Potter_Data_5_,
       var.equal = FALSE)

    Welch Two Sample t-test

data:  FFM_3 by CoinFlip
t = 0.6653, df = 57.312, p-value = 0.5085
alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0
95 percent confidence interval:
 -0.2415295  0.4819141
sample estimates:
mean in group 1 mean in group 2 
       4.307692        4.187500