Centrality & Variability
Due: Sep 20 by 11:59pm
Weight: This assignment is worth 1% of your final grade.
Purpose: The purpose of this assignment is to develop some basic strategies for exploring data sets to gain a greater understanding of the variable types, their centrality, and their variability.
Assessment: This assignment is graded using a check system:
- ✔+ (110%): Responses shows phenomenal thought and engagement with the course content. I will not assign these often.
- ✔ (100%): Responses are thoughtful, well-written, and show engagement with the course content. This is the expected level of performance.
- ✔− (50%): Responses are hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.
Notice that this is essentially a pass/fail system. I’m not grading your writing ability and I’m not counting the number of words you write - I’m looking for thoughtful engagement. One or two sentences is not enough. Write at least a paragraph and show me that you did the readings assigned.
1. Get Organized
Download and edit this template when working through this assignment.
Then unzip the template folder (make sure you unzip it!), then open the .Rproj file to open RStudio. Open the hw3.Rmd
file, take notes, and write some example code as you go through the following.
2. Video on data types & descriptive statistics
This week, we will learn some strategies for exploring data sets to gain a greater understanding of the variable types and their relationships. To get started, open up a notebook (physical, digital…whatever you take notes in best), and take notes while you go through the following readings and video:
- R4DS - 7: Exploratory data analysis: Provides some more “hands on” strategies for exploring data using R and the ggplot2 library.
- Wilke - 5: Directory of visualizations: Provides a quick overview of many common plot types.
- Watch this 20 minute video to learn about some basic data types and descriptive statistics:
3. Exercises
Complete the following RStudio Primer lesson: Exploratory Data Analysis
4. Choosing the right chart
You will want to choose different chart types depending on the relationship or message you want to convey. Fortunately, there are lots of great guides to help you make those choices. View them here.
5. Reflect
Reflect on what you’ve learned while going through these readings and exercises. Is there anything that jumped out at you? Anything you found particularly interesting or confusing? Write at least a paragraph in your hw3.Rmd
file. Here are some suggestions:
- Discuss some of the key insights or things you found interesting in the readings or recent class periods.
- Write about the messiest data you’ve seen.
- Connect the course content to your own work or project you’re working on.
6. Knit
Click the “knit” button to compile your hw3.Rmd
file into a html web page. Then open the hw3.html
file in a web browser and proofread your report. Does all of the formatting look correct?
7. Submit
To submit this assignment, create a zip file of all the files in your R project folder for this assignment. Name the zip file hw3-netID.zip
, replacing netID
with your netID (e.g., hw3-jph.zip
). Then copy that zip file into the “submissions” folder in your Box folder created for this class (the Box folder is named your GW netID).
Page sources: This assignment is inspired by Andrew Heiss’s course on Data Visualization.
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