Statistical Inference 3.1 Methods The components of our multiple linear regression model are the following: Numerical outcome variable y = Review Rating Numerical explanatory variable x1 = Movie Budget Categorical explanatory variable x2 = Movie Rating 3.2 Model Results Table 2. Regression table of linear model of horror movies: (SEE IMAGE ATTACHED) Interpret the regression table
Statistical Inference 3.1 Methods The components of our multiple linear regression model are the following: Numerical outcome variable y = Review Rating Numerical explanatory variable x1 = Movie Budget Categorical explanatory variable x2 = Movie Rating 3.2 Model Results Table 2. Regression table of linear model of horror movies: (SEE IMAGE ATTACHED) Interpret the regression table
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
Statistical Inference
3.1 Methods
The components of our multiple linear regression model are the following:
- Numerical outcome variable y = Review Rating
- Numerical explanatory variable x1 = Movie Budget
- Categorical explanatory variable x2 = Movie Rating
3.2 Model Results
Table 2. Regression table of linear model of horror movies: (SEE IMAGE ATTACHED)
Interpret the regression table
Expert Solution
Step 1
Given information:
Numerical outcome variable y = Review Rating
Numerical explanatory variable x1 = Movie Budget
Categorical explanatory variable x2 = Movie Rating
term | estimate | std_error | Statistic |
intercept | 8.1 | 1.311 | 6.178 |
budget | 0 | 0 | 4.394 |
movie_rating: NOT RATED | -3.544 | 1.314 | -2.697 |
movie_rating: PG | -2.342 | 1.532 | -1.528 |
movie_rating: PG-13 | -3.124 | 1.326 | -2.356 |
movie_rating: R | -3.091 | 1.315 | -2.35 |
movie_rating: TV-14 | -3.735 | 1.375 | -2.716 |
movie_rating: TV-MA | -3.709 | 1.333 | -2.783 |
movie_rating: UNRATED | -3.32 | 1.334 | -2.488 |
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