POS 5698: Data for Campaigns
Week-by-Week Schedule

url: https://rpubs.com/pie-try-ka/pos5698-schedule

All times and dates in the schedule and other course material correspond to Tallahassee’s Eastern Time Zone.

To access the course syllabus, click this link.

WEEK 0 (JANUARY 04): NO CLASS

Classes do not officially start until Wednesday, January 5. So our first meeting will be January 11. This is not an extra week off! Get started on the assignments due next week (see the Week 2 section for details) because they will take considerable time to complete.

Suggested reading:

Grolemund, Garrett, and Hadley Wickham. 2020. R for Data Science, chapters 1 & 2

WEEK 1 (JANUARY 11): INTRODUCTION

Due before 5PM:

1. Join the class’s DataCamp by following the instructions at this link. You must use your my.fsu.edu email address to sign up. Please enter your first and last names in your DataCamp profile to make it easier for us to track your progress.
2. Configure your email and Canvas settings according to these instructions
3. Read this short Reuters article by Elizabeth Culliford
4. Take this introductory survey, which I will use to understand your background and what you hope to get out of this class.
5. Join the class’s RStudio Cloud workspace with this link. Come to class with your RStudio Cloud password ready so you can log in on the lab’s computers.
6. Complete the DataCamp course, “Introduction to R”

• Tip: DataCamp assignments often take around 4 hours to complete. They can be completed in multiple sessions over the course of the week.

Suggested reading:

Grolemund and Wickham chapters 2 and 4

WEEK 2 (JANUARY 18): GETTING TO KNOW YOUR DATA

Due before 5PM:

• DataCamp Course, “Introduction to the Tidyverse”

Suggested reading:

Grolemund and Wickham chapters 3 & 5

WEEK 3 (JANUARY 25): DESCRIBING YOUR DATA

Due before 5PM:

• DataCamp:
  1. “Importing Data in R, part 1” (all chapters)
  2. “Importing Data in R, part 2” (just chapter 5, “Importing data from statistical software packages”)

Suggested reading:

Grolemund and Wickham chapter 11

WEEK 4 (FEBRUARY 01): VISUALIZING YOUR DATA

Due before 5PM:

• DataCamp Course, “Exploratory Data Analysis in R”
• Come to class prepared to discuss ideas you have for your midterm research project. These ideas should include a basic problem you want to address and the data you think you would need to address the problem.

Suggested reading:

Grolemund and Wickham chapters 7 and 28

WEEK 5 (FEBRUARY 08): SURVEY STATISTICS

Due before 5PM:

• DataCamp Course, “Analyzing Election and Polling Data in R”

Suggested reading:

• Intro to confidence intervals
• Pew explains margins of error

WEEK 6 (FEBRUARY 15): GEOGRAPHIC DATA

Due before 5PM:

• On Canvas, submit the assignment, Midterm 1: Proposal.
• DataCamp Course, “Visualizing Geospatial Data in R”

Suggested reading:

Using Geospatial Data in R, by Stefan Jünger

WEEK 7 (FEBRUARY 22): CENSUS DATA

Due before 5PM:

• On Canvas, submit the assignment, Midterm 2: Load your data.
• DataCamp Course, “Analyzing US Census Data in R”

Suggested:

• Read this list Census data resources
• Complete the US Census’s official R course by Ari Lamstein

WEEK 8 (MARCH 01): SURVEY DESIGN

Instead of a Programming Workshop today, we’ll use class time to work through problems you are encountering with your Midterm Project data.

Due before 5PM:

• No required DataCamp this week to give you more time for your analysis draft. Two are suggested below, in case you want more guidance about ggplot2.
• Read Gehlbach, Hunter, and Anthony R. Jr Artino. 2018. The Survey Checklist (Manifesto). Academic Medicine 93(3): 360.

Suggested:

• 10 Things to Know About Survey Design, by Gabriella Sacramone-Lutz
• How to write great survey questions (and avoid common mistakes) by Sarah Fisher
• Writing Survey Questions by the Pew Research Center
• DataCamp: Introduction to Data Visualization with ggplot2
• DataCamp: Intermediate Data Visualization with ggplot2

WEEK 9 (MARCH 08): PRESENTATIONS

Due before 5PM:

• On Canvas,
  • submit the assignment, Midterm 3: Analysis Draft.
  • submit the assignment, Midterm 4: Presentation Slides. Arrive prepared to present your project to the class using the slides submitted to Canvas. I will have the slides ready in the classroom as long as you submit them to Canvas before 5pm.
• Read:
  • 9 Tips For Communicating Science To People Who Are Not Scientists, by Marshall Shepherd
  • The David Attenborough Style of Scientific Presentation, by Will Ratcliff
  • Making Slides, by Kieran Healy

Suggested reading:

(None. Note the above readings are required and the advice is expected to be reflected in your presentations.)

WEEK 10 (MARCH 15): NO CLASS

(SPRING BREAK)

WEEK 11 (MARCH 22): MODELING DATA 1–ESTIMATION AND INTERPRETATION

Due before 5PM:

• On Canvas, provide peer feedback to two classmates for their Midterm 3: Analysis Draft submissions.
• DataCamp Course, “Correlation and Regression in R” (just chapters 1-4)

Suggested reading:

• Grolemund and Wickham chapters 22 & 23
• This guide to getting a campaign+data job.
  • Note 1: this guide is written by progressivedatajobs.org and thus focuses on “progressive” jobs. But if you want a job working for a conservative group, just mentally replace each use of the word progressive with conservative (and vice versa) and it will still be excellent advice.
  • Note 2: I’m suggesting this reading this week because it provides a great overview of the skills you should learn if you want a data-focused job. At this point in the semester, you should be able to understand a lot of the skills it is describing even if you have yet to learn those skills. You can use the advice to focus what you learn the rest of this semester (and into the future).

WEEK 12 (MARCH 29): MODELING DATA 2–MODEL SELECTION AND OVERFITTING

Due before 5PM:

• On Canvas, submit the assignment, Midterm 5: Full Report.
• DataCamp Course, “Modeling with Data in the Tidyverse”

Suggested reading:

Grolemund and Wickham chapters 24 & 25

WEEK 13 (APRIL 05): MISSING DATA, MISCODED DATA, AND OTHER PROBLEMS

Due before 5PM:

• On Canvas, submit the assignment, Final 1: Proposal+Load your data.
• Complete these three DataCamp assessments to the best of your ability. Do not worry if you struggle, your grade is based on completing these assessments, not the score you receive.
  1. Importing & Cleaning Data with R
  2. Data Manipulation with R
  3. Data Visualization with R
• After completing the three DataCamp assessments above, use the results and your interests to choose and complete one or more of the following DataCamp courses:
  1. Practice your basic Tidyverse skills
  2. Practice exploratory data analysis with a well-designed case study
  3. Practice making prettier, more informative plots
  4. Learn how to conduct text analysis
  5. Learn some more advanced programming concepts like loops

Suggested reading:

• Handling Missing Values in R using Tidyr, by Arimoro Olayinka
• Grolemund and Wickham chapter 12

WEEK 14 (APRIL 12): TEXT AS DATA

Instead of a Programming Workshop today, we’ll use class time to work through problems you are encountering with your Final Project data.

Due before 5PM:

• No DataCamp this week to give you more time for your analysis draft.
• On Canvas, submit the assignment, Final 2: Analysis Draft.

Suggested reading:

Skim Text Mining with R, by Julia Silge and David Robinson

WEEK 15 (APRIL 19): PRESENTATIONS

Due before 5PM:

• On Canvas:
  • provide peer feedback to two classmates for their Final 2: Analysis Draft submissions.
  • submit the assignment, Final 3: Presentation Slides. Arrive prepared to present your project to the class using the slides submitted to Canvas. I will have the slides ready in the classroom as long as you submit them to Canvas before 5pm.

WEEK 16 (APRIL 26): NO CLASS, FINALS WEEK

Due before 5PM:

• On Canvas, submit the assignment, Final 4: Full Report.