0308_lab4.Rmd

# Lab 4: Personality and green reputation {#lab04}

In this lab, You will analyze data looking at the relationship between 
**green reputation** and three personality traits--
**compassion**, **intellectual curiosity**, and **openness to experiences**.
The dataset includes data from **students** and **non-students**.

## Getting started

Make a new RMarkdown script for this lab. 
In the *setup* chunk at the top of your scripts,
load the packages needed for this lab. 

Download the 2 data files for this lab and save them in the `data` folder of your
GitHub folder.

  1. [green_dictionary](https://raw.githubusercontent.com/bwiernik/progdata-class/master/data/green_dictionary.csv)
  2. [green_data](https://raw.githubusercontent.com/bwiernik/progdata-class/master/data/green_data.csv)
  
Add a chunk with these lines chunk to your RMarkdown script to import the data.

```{r, eval = FALSE}
dictionary <- readr::read_csv(here::here("data", "green_dictionary.csv"))
green_data <- readr::read_csv(here::here("data", "green_data.csv"))
```

For your assignment, do the following.

  1. Inspect the item responses (e.g., with graphs or by summarizing distinct values). 
     Is anything unusual?
  2. Compute total scores for the four scales. 
     Recode variables as needed.
  3. Rescale the variables so that they go from 0-100 instead of the original range.
     Name the recaled variables `*_pomp`.
  4. Make plots that illustrate the distributions of the 4 POMP-scored variables.
  5. Make scatterplots showing the relationships between **green reputation** and each personality trait.
     Include trend lines for **students** and **non-students**.
     What do these plots show?
  6. Compare **green reputation** for students and non-students using a **rainfall plot** (bar + density + data points).
  7. Compute a summary table of means, SDs, medians, minima, and maxima for the four total scores for students and non-students.