oneSampleTTest: One sample t-test

Description

Runs a one-sample t-test and prints the results in a readable format.

Usage

oneSampleTTest(x, mu, one.sided = FALSE, conf.level = 0.95)

Value

Prints a summary showing the variable name, descriptive statistics, null and alternative hypotheses, test results (t-statistic, degrees of freedom, p-value), a confidence interval, and Cohen's d as a measure of effect size. The underlying results are also returned as a list, so the output can be assigned to a variable and inspected if needed.

Arguments

x: A numeric vector containing the data to be tested.
mu: The hypothesised population mean to test against.
one.sided: Set to FALSE (default) for a two-sided test. Set to "greater" if you expect the population mean to be above mu, or "less" if you expect it to be below.
conf.level: The confidence level for the confidence interval. The default is 0.95 for a 95% interval.

Details

Runs a one-sample t-test comparing the mean of x to the hypothesised value mu, and prints the results in a beginner-friendly format. The calculations are done by t.test and cohensD. Missing values in x are removed with a warning.

Examples

Run this code

likert <- c(3, 1, 4, 1, 4, 6, 7, 2, 6, 6, 7)

# two-sided test (the default)
oneSampleTTest(x = likert, mu = 4)

# one-sided test: is the mean greater than 4?
oneSampleTTest(x = likert, mu = 4, one.sided = "greater")

# wider confidence interval
oneSampleTTest(x = likert, mu = 4, conf.level = 0.99)

# missing values are removed with a warning
likert <- c(3, NA, 4, NA, 4, 6, 7, NA, 6, 6, 7)
oneSampleTTest(x = likert, mu = 4)