Test a null hypothesis involving the means of two populations by performing a Student's T-test.
The t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. Compute a t-test by selecting a numerical test variable and a categorical grouping variable. The null hypothesis can be configured using the other parameters, for example you can choose between a one sided or two sided test and change the difference in means expected in the null hypothesis.
The first section of the output is the printed output of a
t.test run in R. There are more details on this printed output in the R documentation for t.test. The output also includes a plot comparing the densities and means of the selected groups.
|test_var||Yes||Column Input. Integer, Decimal||Numerical variable upon which the t.test will be run against.|
|group_var||Yes||Column Input. Text, Integer, Boolean, DateTime, Date||Categorical variable upon which grouping will occur.|
|mu||Yes||Decimal||Value of which to compare the sample mean.|
|alternative||Yes||Text selector. Default to two-sided.||Select from a greater, less or two-sided t-test.|
|paired||Yes||Boolean||Toggle between computing a paired t-test or not.|
|confidence_level||Yes||Decimal. Ranging from 0.5 to 0.99. Default to 0.95.||Set your t-test confidence interval.|
- More about Density Plots
- [About the ggplot2 library](https://ggplot2.tidyverse.org/" target="_blank" rel="noopener)