Learn R: T-tests

Load Packages

Haven

Haven enables R to read and write various data formats used by other statistical packages by wrapping the fantastic ReadStat C library written by Evan Miller.

https://www.rdocumentation.org/packages/haven/versions/2.5.1

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

Loading required package: haven

Tidyverse

The tidyverse makes it easy for us to tidy, clean, manipulate and rearrange our data.

https://www.rdocumentation.org/packages/tidyverse/versions/1.3.2

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

Loading required package: tidyverse

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0      ✔ purrr   1.0.1 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.5.0 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

Import Data

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

T-Tests

t.test(formula = FFM_1 ~ CoinFlip,
       data = dataset,
       var.equal = FALSE)

    Welch Two Sample t-test

data:  FFM_1 by CoinFlip
t = -2.419, df = 76.753, p-value = 0.01793
alternative hypothesis: true difference in means between group 1 and group 2 is not equal to 0
95 percent confidence interval:
 -1.0412385 -0.1009527
sample estimates:
mean in group 1 mean in group 2 
       3.307692        3.878788