subtitle: A Review Specific to the State of Arizona in 2025

Presentation on A/B testing.

This presentation demonstrates simple linear regression using the mtcars dataset to model the relationship between car weight and fuel efficiency. It includes model interpretation, regression and residual plots, and an interactive visualization to explore the data.

Define variables: 1) Dependent variable (the outcome you are interested in) (x) 2) Independent variable(s) (the variables which you think affect the outcome) (y) Define your hypotheses: 1) Null hypothesis - there is NO EFFECT of y on x 2) Alternative hypothesis - there is SOME EFFECT of y on x Give me a few good paragraphs explaining your hypothesis and identifying your variables.

This a first try to Publish in RPubs to learn how to use the tool.

I believe I submitted the wrong HW - I was supposed to submit HW 4 which was due 3/23. From the data you have chosen, select a variable that you are interested in 1. Use pastecs::stat.desc to describe the variable. Include a few sentences about what the variable is and what it's measuring. 3) Remove NA's if needed using dplyr:filter (or anything similar) 4) Provide a histogram of the variable (as shown in this lesson) 5) transform the variable using the log transformation or square root transformation (whatever is more appropriate) using dplyr::mutate or something similar 6) Provide a histogram of the transformed variable 7) submit via rpubs on CANVAS