Exercise

# Two-sample t-test

A **two-sample t-test** is used to test if the means of two populations equal.

The examples of analyses that quantify the impact of a factor include testing *a pharmaceutical drug on patients* or *a marketing campaign on demand*.

Recall that few **assumptions** need to be met to carry out a **two-sample t-test**:

- Random samples
- Independent observations
- Normally distributed underlying data
- Homogeneity of variances

The former two assumptions need to be met at the stage of designing the experiment.
The latter two assumptions can be tested using **the Shapiro-Wilk test** and **Bartlett's test** respectively.

A company provided you with the `df`

data frame. The `sample`

column indicates the sample, and the `value`

column contains numerical data. The `dplyr`

package is available in your environment.

Instructions 1/4

**undefined XP**

- Print the first 6 rows of
`df`

. - Retrieve values and run the Shapiro-Wilk test on the first sample.
- Retrieve values and run the Shapiro-Wilk test on the second sample.