walkthrough_p: Walkthrough p-values

In janhove/cannonball: Tools for Teaching Statistics

Walkthrough p-values

Description

This function produces a step-by-step demonstration of a significance test for a two-group comparison.

Usage

walkthrough_p(n = 10, diff = 0, sd = 1, showdata = FALSE, pedant = FALSE)

Arguments

n	The number of data points per group.
diff	The boost that participants in the intervention group receive.
sd	The standard deviation of the normal distributions from which the data are drawn.
showdata	Do you want to output a dataframe containing the plotted data (TRUE) or not (FALSE, default)?
pedant	Do you want to run the significance test in pedant mode (TRUE) or not (FALSE, default)? See Details.

Details

Data are generated from a normal distribution with the requested standard deviation. Then, the data points are randomly assigned to two equal-sized groups. Data points in the intervention group receive a boost as specified by diff. Finally, a significance test is run on the data.

By default, the significance test is a two-sample Student's t-test. Technically, the p-value from this test is the probability that a t-statistic larger than the one observed would've been observed if only chance were at play, but the walkthrough text says that is the probability that a mean difference larger than the one observed would've been observed if only chance were at play. That is, I use the t-test as an approximation to a permutation test. Switch on pedant mode if you want to run a permutation test.

Examples

## Not run: 
walkthrough_p(n = 12, diff = 0.2, sd = 1.3)

# Save data and double check results
dat <- walkthrough_p(n = 10, diff = 0.2, sd = 2, showdata = TRUE)
t.test(score ~ group, data = dat, var.equal = TRUE)

# Run in pedant mode (= permutation test)
dat <- walkthrough_p(n = 13, diff = 1, sd = 4, pedant = TRUE, showdata = TRUE)
t.test(score ~ group, data = dat, var.equal = TRUE)

## End(Not run)

janhove/cannonball documentation built on Feb. 19, 2025, 5:13 a.m.