T Tests

Load packages

haven

import and export ‘SPSS’ , ‘Stata’ and ‘SAS’ files.

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

Loading required package: haven

tidyverse

the tidyverse is a opinionated collection of R packages designed for data science.

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   3.4.2     ✔ 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

ImportData

SPSS

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

t-test

t.test(formula = FFM_31 ~ CoinFlip,
       data = dataset,
       var.equal = FALSE)

    Welch Two Sample t-test

data:  FFM_31 by CoinFlip
t = 0.18361, df = 65.116, p-value = 0.8549
alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0
95 percent confidence interval:
 -0.4480418  0.5387677
sample estimates:
mean in group 1 mean in group 2 
       3.593750        3.548387