Activity 06 - Logistic Regression

This activity is intended to be completed over three 75-minute class meetings. On our Blackboard course site you were provided with items to read, watch, and do prior to attempting this activity.

In this repository/directory, you should see five items:

• README-img - a folder containing images that I am embedding within this README.md file and other files. You do not need to do anything with this.
• .gitignore - a file that is used to specify what Git can ignore when pushing to GitHub. You do not need to do anything with this.
• README.md - the document you are currently reading.
• day01-logistic - a folder that contains items for you to complete during the first class meeting.
• day02-multinomial - a folder that contains items for you to complete during the second week of this activity.

We will explore most of these items over this week. Before doing that, you will first make your own copy of this repository.

Check in

Do you want an interactive way to check your understanding outside of class? Remember that these are a good way to check your foundation understanding and were created by Benjamin Baumer (associate professor at Smith College), in collaboration with the OpenIntro team and others. The following tutorials will provide you with an applied approach to our topics (reorganized to better correspond with our readings):

• ISLR 3.2 & 3.3 - Logistic regression
• There is no interactive tutorial that corresponds to multinomial logistic regression.

Task 1: Forking & cloning

Forking

Read these directions first, then work through them. In this GitHub repo (i.e., my repo):

1. Click on the Fork icon near the upper-right-hand corner. You will be taken to a Create a new fork screen.
2. Verify that your GitHub username is selected under Owner and that the Repository name is activity06-logistic-regression with a green check mark (this verifies that you do not already have a GitHub repository with this name).
3. You may provide a Description if you would like. This is a way to provide some additional, more descriptive, meta information related to the things you did. I like to provide a brief description of what happened.
4. Verify that Copy the main branch only is selected.
5. Click on the green Create fork button at the bottom of this page.

You should be taken a copy of this repo that is in your GitHub account. That is, your page title should be username/activity06-logistic-regression, where username is replaced with your GitHub username. Directly below this, you will see the following message:

forked from gvsu-sta631/activity06-logistic-regression

You will complete the rest of this activity in your forked copy of the activity06-logistic-regression repo.

Cloning

Read these directions first, then work through them. Note that you will be switching between RStudio and your GitHub repo (that you previously forked).

1. In RStudio, click on the icon (the icon below the Edit drop-down menu).
2. Click on Version Control on the New Project Wizard pop-up.
3. Click on Git and you should be on a “Clone Git Repository” page.
4. Back to your activity06-logistic-regression GitHub repo, click on the green Code button near the top of the page.
5. Verify that HTTPS is underlined in orange/red on the drop-down menu, then copy the URL provided.
6. Back in RStudio, paste the URL in the “Repository URL” text field.
7. The “Project directory name” text field should have automatically populated with activity06-logistic-regression. If yours did not (this is usually an issue on Macs),
   • Click back into the “Repository URL” text field.
   • Highlight any bit of this text (it does not seem to matter what or how much).
   • Press Ctrl/Cmd and the “Project directory name” should now have automatically populated with activity06-logistic-regression.
8. Browse to STA 631/Activities (assuming you followed my opinionated file structure from earlier in the semester), then click Choose.
9. Click on Create Project.

Your screen should refresh and the Files pane should say that you are currently in your activity06-logistic-regression folder that currently has the same files and folders as your GitHub repo. If you are asked for your GitHub credentials, provide your GitHub username and your PAT (not your password).

Check in

Take a moment to reflect on what is possibly your second time doing this forking process.

• How is this process going for you? Is it “muscle memory” yet?
• What is easier since last week?
• What do you still need help remembering?

We will use a dataset with information from résumés and job callbacks.

Task 2: Odds and logistic regression

Read these directions first, then work through them.

1. In your activity06-logistic-regression repo folder/directory, locate and click into the day01-logistic subfolder.
2. In the day01-logistic subfolder, you will be greeted by a new README.md file. Do your best to complete the tasks/directions provide in this subfolder by 11:59 pm (EST) on Fri, Feb 23.
3. Ask questions in class as you are working. If you need to finish this up outside of our class meetings, remember that you can use our Teams workspace (linked on Blackboard), and post questions/issues in the Muddy channel. If someone else already posted what you though was muddy, add any clarification to their post and give them a “+ 1” 👍. Remember that this space is for conversations as well as posting questions. Read through your peers’ muddy posts and do your best to provide help.

The rest of this README document contains tasks/directions for the second class meeting of this week.

Task 3: Mulinomial logistic regression

You will work in activity06-multinomial.Rmd file for this portion of the activity as we are working with a different dataset. Read these directions first, then work through them.

1. In your activity06-logistic-regression repo folder/directory, locate and click into the day03-multinomial subfolder.
2. In the day03-multinomial subfolder, you will be greeted by a new README.md file. Do your best to complete the tasks/directions provide in this subfolder by 11:59 pm (EST) on Fri, Mar 1.
3. Ask questions in class as you are working. If you need to finish this up outside of our class meetings, remember that you can use our Teams workspace (linked on Blackboard), and post questions/issues in the Muddy channel. If someone else already posted what you though was muddy, add any clarification to their post and give them a “+ 1” 👍. Remember that this space is for conversations as well as posting questions. Read through your peers’ muddy posts and do your best to provide help.

Attribution

This document is based on materials from OpenIntro and Dr. Maria Tackett (Duke University).

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.