IT 223

Fall 2026

Craig Miller

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Weekly Notes

• Week 0
• Week 1
• Week 2
• Week 3
• Week 4

Assignments

• Assignment 1
• Assignment 2
• Assignment 3
• Assignment 4

Technical References

• Course text (OpenStax Statistics)
• OpenIntro Statistics
• R tutorial

Assignment 4
Regression Analysis
Submit before 11:30 Sunday October 11

Overview

How does the ability to trace code to predict its output correspond to the ability to write code? For this assignment, you will use linear regression to explore the relationship between an assessment of code tracing and code writing.

Analysis tasks

1. Download the zip folder of files for assignment 4 and review its contents. The csv file contains two columns of data from a CSC 242 midterm. One column corresponds to an assessment of code tracing (maximum possible is 28) and one for a code writing problem (maximum possible is 7).
2. Using the line-fit-explorer app, load in the csv file and work on identifying good fit values for the y-intercept and the slope. Summarize your experience. (When writing your overall summary for the assignment, include highlights from this experience.)
3. Using R, perform a linear regression analysis on the relationship between the tracing assessment (x value) and the code-writing assessment (y value). The analysis should include a plot, a model summary and plots of the model.
4. Summarize your analysis. Be sure to address the description of the model, how well the values correlate, and whether the linear model provides an appropriate fit.

Deliverable

Create word or pdf file that contains the following:

1. A summary statement of your experience completing this assignment. It should contain a major finding from the paragraph of the last task (not the whole paragraph). Place this summary statement at the top of your document.
2. Your clearly labeled answers to questions and problems
3. Any additional details or output that you would like to include or document but are too long to insert among your answers.

Grading

The assignment is worth 5 points. Full credit will be awarded to complete, accurate and well presented submissions. Points will be deducted for the following:

• Summary statements that do not reference concepts or details specific to the assignment
• Summary statements without meaningful experiences and explanations
• Incomplete answers
• Inaccuracies (possibly excepting minor ones)