Exercise

# ANOVA for plant growth

In this exercise, you will perform **a one-way ANOVA** to compare means across three groups.

Such a task might pop up during the interviews for various sectors, including *engineering*, *marketing*, and *medical services*.

Recall that **the assumptions of ANOVA** are:

- Independence of cases
- Normal distributions
- Homogeneity (equality) of variances

You can check the two last assumptions with **the Shapiro-Wilk test** and **Bartlett's test** respectively.

The null **hypothesis** of a one-way ANOVA states that the means across groups are equal.
$$ H_0: \mu_1 = \mu_2 = ... = \mu_n $$

Use `oneway.test()`

to perform ANOVA in this exercise.

Watch out! So far, we've used `tapply()`

to compute descriptive statistics across groups. We can use this function to perform **statistical tests** across groups, too!

Instructions 1/4

**undefined XP**

- Perform a normality test of
`weight`

on the data for each`group`

using the`PlantGrowth`

data frame. - Test if variances of
`weight`

across groups are equal.