t-test

Last Updated: 21, November, 2024 at 09:05

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0      ✔ purrr   1.0.2 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.1      ✔ stringr 1.4.1 
## ✔ readr   2.1.3      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

The most boring data in the world…

data <- read_csv('data/bands.csv')

## New names:
## Rows: 9 Columns: 3
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," dbl
## (3): ...1, heated, ambient
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...1`

Note: here we treat the data as collected on separate rubber bands. This is, we run a two sample t-test.

t.test(data$ambient, data$heated)

## 
##  Welch Two Sample t-test
## 
## data:  data$ambient and data$heated
## t = -0.86861, df = 15.814, p-value = 0.3981
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -21.805078   9.138412
## sample estimates:
## mean of x mean of y 
##  251.2222  257.5556

c1 <- adjustcolor( "red2", alpha.f = 0.25)
c2 <- adjustcolor( "green2", alpha.f = 0.25)
hist(data$ambient, col=c1, xlim = c(200, 350), ylim = c(0, 6))
hist(data$heated, col=c2, add=TRUE)