Project: Variable Analysis & Visualizations Check-In

Python

Tip

This assignment must be completed in the assignment.ipynb file provided in the GitHub repository you created when you accepted this assignment.

I will NOT grade any other file.

These instructions are also included in the README.md file in the repository for your reference.

For more on connecting to the GitHub repository, see below.

Project Overview

In this project check-in you will perform variable analysis and represent the analysis with accompanying visualizations.

Criteria:

  • Perform one Pearson r correlation test on your data.
  • Perform on t-test on your data.
    • Include any accompanying tests necessary for interpretation.
  • Perform one ANOVA test on your data.
    • Include any accompanying tests necessary for interpretation.
  • Explain why you chose the variables and interpret your results.
  • Include at least one visualization for each test that you conduct to demonstrate the results.
    • Include explanations for why you chose the visualizations you did.
  • Include a narrative that interprets the results.
  • The narrative should interweave the explanation for the variable choices, the visualization, and the interpretation.

Variable Analysis & Visualizations Rubric

Criteria 4 Points 3 Points 2 Points 1 Point
Correlation Test The submission (1) correctly performs a Pearson r correlation (2) on the appropriate variables, and (3) includes the coefficient of determination. The submission does not include include one of the three required criteria. The submission does not include include two of the three required criteria. The submission does not include a Pearson r correlation test.
T-Test The submission (1) correctly performs a t-test (2) on the appropriate variables, and (3) includes any accompanying tests necessary for interpretation. The submission does not include one of the three required criteria. The submission does not include two of the three required criteria. The submission does not include a t-test.
ANOVA Test The submission (1) correctly performs an ANOVA test (2) on the appropriate variables, and (3) includes any accompanying tests necessary for interpretation. The submission does not include one of the three required criteria. The submission does not include two of the three required criteria. The submission does not include an ANOVA test.
visualization Choices The submission includes the appropriate visualization to demonstrate the results of each statistical test and uses them to effectively demonstrate the results. The submission fails to do this for one of the visualizations. The submission fails to do this for two of the visualizations. The visualizations do not align to the statistical tests.
Visualization Annotation Layers The submission includes all annotation layers necessary to effectively communicate the results of each visualization. The submission fails to include one of the necessary annotation layers for the visualizations. The submission fails to include two of the necessary annotation layers for the visualizations. The submission does not include any necessary annotation layers for the visualizations.
Visualization Text The submission includes the associated stats in the visualization text to effectively communicate the results of each statistical test. The submission fails to include the associated stats in the visualization text for one of the tests. The submission fails to include the associated stats in the visualization text for two of the tests. The submission does not include the associated stats in the visualization text for any of the tests.
Interpretation The submission provides a thorough and accurate interpretation of all results and clearly relates them to the research question. The interpretation is either not thorough or not accurate, or the connection to the research question is only partially clear. The interpretation is minimal and/or inaccurate, with little connection to the research question. The submission does not provide any interpretation of the results.
Narrative The submission is written in narrative form using markdown to describe the code and effectively integrates the results within the narrative. The submission is written in narrative form using markdown to describe the code, but the integration is not complete. The submission lacks clear narrative form, and the integration of results is minimal. The submission is disorganized, lacks narrative form, and does not integrate results.

GitHub Classroom

This assignment uses GitHub Classroom. GitHub Classroom is a tool that helps instructors manage coding assignments using GitHub repositories. When you accept the assignment, GitHub Classroom will create a private repository for you where you can work on your code. To complete this assignment you will have to accept the assignment, clone the repository to your local machine, complete the assignment, and then commit and push your changes back to GitHub.

To accept the assignment, go to the assignment page on Canvas and click on the link to create the GitHub repository.

Note

Part of this assignment is not just completing the coding tasks, but also learning how to use GitHub and Git for version control. Make sure to follow the instructions carefully and reach out to me if you encounter any issues.

Understand, problems with Git/GitHub are not an excuse for late work. Plan ahead to ensure you have time to resolve any issues that may arise. In industry, version control is an essential skill, and being proficient with these tools is crucial for collaboration and project management. Moreover, technology issues (including those with GitHub) will never be accepted as an excuse for missing deadlines. This is a programming class. The technology is part of the assignment.

If technology difficulties arise, I’m happy to help, but before deadlines (not after).

Cloning the Repository

Once you have accepted the assignment, a new repository titled - will be created in your GitHub account. You can log in to GitHub to view the repository. You will need to clone this repository to your local machine to work on the assignment. Follow these steps to clone the repository:

  1. Open VS Code
  2. Press Ctrl+Shift+P (or Cmd+Shift+P on Mac) to open the command palette.
  3. Type Git: Clone and select it.
  4. Select Clone from GitHub...
  5. You might be prompted to sign in to GitHub if you haven’t already.
  6. After signing in to GitHub, you will need to follow steps 1-4 again to clone the repository.
  7. You should receive a list of your repositories. Select the repository for this assignment.
    1. If you do not see your repository, you can copy the URL from GitHub and paste it into the prompt in VS Code.
  8. Choose a local directory where you want to clone the repository.
    1. Choose the folder location carefully. File management is incredibly important in programming, and it is best to keep all your assignments for this class in one folder.
    2. Make sure NOT to clone the repository into another repository.
  9. Click Select Repository Location to complete the cloning process.

Committing and Pushing Changes

In order to submit your assignment, you will need to commit any changes you make to your local repository and push them to GitHub. Committing saves your changes to the local repository, while pushing uploads those changes to the remote repository on GitHub. In other words, just saving your files is not enough. Saving updates the files on your computer, but when you commit those saves, you are creating a snapshot of your project at that point in time. Think of a commit like a save point in a video game that you can always return to. Remember, you can commit multiple changes to multiple files at once You should commit your changes to the repository often, especially after completing significant portions of the assignment. To do so, follow these directions.

  1. Click the Source Control icon in the Activity Bar on the side of VS Code (it looks like a branch with a dot at the end). You should see a list of files that have been changed.
  2. Stage changes to be committed. Not all files need to be in every commit. You can stage individual files by hovering over the file name and clicking the plus (+) icon that appears, or you can stage all changes at once by clicking the plus (+) icon next to the “Changes” header.
  3. Enter a commit message in the text box at the top of the Source Control panel that describes the changes you made. A good commit message is concise yet descriptive, such as “Completed function to calculate average” or “Fixed bug in data processing loop.”
  4. Press the blue button below the commit message box that looks like a checkmark to commit your changes.
  5. After committing, these changes are still only saved locally. The blue button below the commit message input box now states “Sync Changes” with an up and down arrow icon. Click this button to push your committed changes to the remote repository on GitHub. You may be prompted to sign in to GitHub again if you haven’t done so recently.
  6. Check the GitHub repository online to ensure your changes have been pushed successfully. If you cannot see your changes online, try refreshing the page. If you still cannot see your changes, the process was not completed successfully, and you should try pushing again.