Midterm Instructions

Instructions

• You are expected to complete this assignment entirely on your own
  • You may ask me clarification questions only, no coding or content related questions
  • You may use any course materials, including your labs, any direct link on my website (https://rebelskyw.cs.grinnell.edu/sta-230-fall-2024-2/), and the ggplot2 cheat sheet: https://posit.co/wp-content/uploads/2022/10/data-visualization-1.pdf
  • You may not discuss the assessment with your classmates
• This is an in class Exam. You must submit your answer (or what you have so far) by the end of class today
  • There will be no class on Thursday 03 October to allow for extra time if needed

Task

Your goal is to replicate both data visualizations given as closely as possible. You may still be able to get points if your visualization is nearly correct. These visuals can be made using techniques covered in our labs and homework. Visualization 1 needs to be turned in by the end of class. When you’ve turned in your solution to Visualization 1 you may pick up the second visualization.

Submitting your solutions

• When you have finished the first visualization: Submit (via gradescope) an R script and only an R Script – no html or R Markdown – that includes all of the code needed to recreate the first visualization. Submit this to Midterm Part 1 Day 1
• You can then pick up the second visualization. At the end of class, submit what you have so far to Midterm Part 2 Day 1
• If you do not finish the second visualization, you may work on it in class on Thursday. All of your work on Thursday should be submitted to Midterm Part 2 Day 2

Visualization 1

Background: These data come from a real study conducted in an advanced driving simulator looking at performance of subjects who had acutely consumed cannabis. Each subject engaged in four drives, labeled “RT1” through “RT4”. The first, “RT1”, was a baseline drive where the subject was sober. After this drive the subject consumed cannabis and engaged in similar drives at approximately 30-min, 90-min, and 180-min after dosing. These drives were split into a series of defined events, and various aspects of driving performance were recorded for each event.

Data:

drives = read.csv("https://remiller1450.github.io/data/drives.csv")

“drives.csv” contains participants IDs for select participants and the number of lane departures on the left and right side of the lane within 3 different defined segments of the drive (recorded by “EventNum”)

Visualization 2

Background:

This data consists of F2024 course data.

Data: The data for this portion is the Fall 2024 Course data used in the SQL Lab (Lab 9).