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 (SEE ATTACHED REGRESSION TABLE TO ANSWER 3.4
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 (SEE ATTACHED REGRESSION TABLE TO ANSWER 3.4
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.2: Representing Data
Problem 6PPS
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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
(SEE ATTACHED REGRESSION TABLE TO ANSWER 3.4)
3.4 Inference for multiple regression
Using the output of our regression table we’ll test the null hypothesis for our numerical explanatory variable.
![A trople. 3x7
term
<chr>
intercept
budget
movie_rating: NOT RATED
movie_rating: PG
movie_rating: PG-13
movie_rating: R
movie_rating: TV-14
movie_rating: TV-MA
movie_rating: UNRATED
9 rows | 1-4 of 7 columns
estimate
<dbl>
8.100
0.000
-3.544
-2.342
-3.124
-3.091
-3.735
-3.709
-3.320
std_error
<dbl>
1.311
0.000
1.314
1.532
1.326
1.315
1.375
1.333
1.334
statistic
<dbl>
6.178
4.394
-2.697
-1.528
-2.356
-2.350
-2.716
-2.783
-2.488
1
F](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fd02fd946-8ac7-4999-b0b8-32882e94e9e4%2F31c1de81-564b-4db1-88a1-82c1abb475f0%2Fw15vi3_processed.jpeg&w=3840&q=75)
Transcribed Image Text:A trople. 3x7
term
<chr>
intercept
budget
movie_rating: NOT RATED
movie_rating: PG
movie_rating: PG-13
movie_rating: R
movie_rating: TV-14
movie_rating: TV-MA
movie_rating: UNRATED
9 rows | 1-4 of 7 columns
estimate
<dbl>
8.100
0.000
-3.544
-2.342
-3.124
-3.091
-3.735
-3.709
-3.320
std_error
<dbl>
1.311
0.000
1.314
1.532
1.326
1.315
1.375
1.333
1.334
statistic
<dbl>
6.178
4.394
-2.697
-1.528
-2.356
-2.350
-2.716
-2.783
-2.488
1
F
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