I'm looking for a concise, well-commented R ipynb that performs a linear regression on a set of clean numerical data. My stated goal is "Linear Regression (R Programming)", meaning | want the full workflow-from loading the data, fitting the model, checking assumptions, through to interpreting and visualising the results-carried out in native R (tidyverse, stats, or other base functions are all fine).
This project focuses on understanding what qualifies as a linear regression model. Participants will be asked to evaluate a set of candidate models and determine whether they are linear in the parameters. The goal is to reinforce the fundamental principle that linear regression is about linearity in the coefficients, not necessarily in the predictor variables.
Deliverables:
• A ipynb file
Acceptance criteria:
• Script runs without errors in Jupyter
If you can deliver this cleanly and quickly, let's get started right away.
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