T-tests

Load Packages

haven

Import and export SPSS, STATA, SAS FILES

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

Loading required package: haven

tidyverse

The tidyverse is a collection of packages that make it easier for us to tidy and manipulate our data

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   3.5.1     ✔ 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 <- read_sav("https://osf.io/kd4ej/download")

t-test

t.test(formula = FFM_7 ~ CoinFlip, data = dataset, var.equal = FALSE)

    Welch Two Sample t-test

data:  FFM_7 by CoinFlip
t = 1.0719, df = 45.545, p-value = 0.2894
alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0
95 percent confidence interval:
 -0.1748486  0.5729255
sample estimates:
mean in group 1 mean in group 2 
       4.261538        4.062500