Learning R-test

Load packages

if(!require(haven)){
install.packages("haven", dependencies = TRUE)
  library(haven)
}

Loading required package: haven

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

Loading required package: tidyverse

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.0     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Import Data

dataset.spss <- read_sav ("Harry Potter Data.sav")

T-test

t.test(formula = FFM_3 ~ CoinFlip,
       data = dataset.spss,
       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