T-tests

Load Packages

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

Loading required package: haven

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

Loading required package: tidyverse

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.2     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.2     ✔ tidyr     1.3.0
✔ 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_12 ~ CoinFlip,
       data = dataset,
       var.equal = FALSE)


    Welch Two Sample t-test

data:  FFM_12 by CoinFlip
t = 0.68937, df = 75.691, p-value = 0.4927
alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0
95 percent confidence interval:
 -0.2961112  0.6095727
sample estimates:
mean in group 1 mean in group 2 
       1.969231        1.812500