Assingment

Dr. Alam, CS 445

Assignment on Multiple Regression (Chapter 7)

Please complete the exercise 7.9 "Excel MLR Practice: Disney Movie Revenue" found https://app.myeducator.com/reader/web/1382fc/chp07/kz4jl/ for Chapter 7 assignment, but in R instead of Excel. To do this, download the file disney_movies_total_gross.csv from the book under Resource Files and load it into RStudio. As you work on each question from the book, post your answer in the book.

Here are the steps in more detail:

1. Download the file disney_movies_total_gross.csv from the book under Resource Files.

Open RStudio and load the data file.

2. Once the data file is loaded, you can start working on the questions in the exercise.

3. To answer each question, write R codes to perform the necessary tasks and then post your answer in the book.

As you work on the assignment, please take a look at the lecture (5 minutes long, link provided below) on how to interpret the coefficients for categorical variables with more than two levels in regression models. Please log into MyJSU before clicking on the link.

https://www.linkedin.com/learning/introduction-to-stata-15/categorical-explanatory-variables-in-ols?u=36441276

The lectures I posted on Canvas explain how to interpret a model result mostly using continuous variables, except for the Gender variable, which has two levels (0/1).

The lecture directed by the link above explains the output of a model with a categorical variable with more than four levels. This lecture will help you to interpret the coefficients of your model in the assignment.

Deliverables:

1. Please create a separate Word file that will include an interpretation of your model results for Question #7. Specifically, please interpret the results for the coefficients, Std. Error, t-value, p-value for each of the variables (days_since_release, mpaa_rating) produced in R. My lectures posted on Canvas can help you with the answers to this question.

2. For question 17, upload your R file to Canvas, with your code separated by question number and with the question number included before the code for that question.

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