---
title: "Assignment: Analysis of Variance (ANOVA)"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

Eysenck (1974) ran a study in which participants were required to recall a list of words. The conditions varied in terms of whether subjects simply counted the number of letters in a word ("Counting", `GROUP` = 1), thought of a rhyming word ("Rhyming", `GROUP` = 2), thought of an appropriate adjective ("Adjective", `GROUP` = 3), created images of the word ("Imagery", `GROUP` = 4), or was told to study the words for later recall ("Intentional", `GROUP` = 5). The dependent variable was the number of words recalled on a test trial. These data are in `eysenck1974.csv` file.

# Exercise 1

Load the data and recode `GROUP` column as a factor with appropriate labels.

```{r}
# Your code here
```

# Exercise 2

Prepare a table with descriptive statistics (mean, median, standard deviation, sample size) for each condition. You can improve the look of the table by using `flextable`, `kable` or `pander` packages (look them up; here it would be tempting to just use ChatGPT to produce the tables; resist the temptation and read the documentation).

```{r}
# Your code here
```

# Exercise 3 

Make a visualization of the data. You can make barplot, line plot or boxplots using your favorite package. Mine is `ggpubr` but you can also try other packages: `plotly` and `rbokeh` are worth trying and quite impressive from the point of view visual flare and interactivity. 

```{r}
# Your code here
```

# Exercise 4

Run a one-way analysis of variance on these data and appropriate *post-hoc* test. Write the results section (preferably in APA or similar style).

```{r}
# Your code here
```

*Your answer here*

# Exercise 5

Check the assumptions of the ANOVA using diagnostic tools that we covered during classes on linear regression. What are your conclusions?

```{r}
# Your code here
```

*Your answer here*