Question 4.Regression Analysis: Weekly Gross Revenue ($1000s) versusTelevison Advertising ($1000s), Newspaper Advertising($1000s). Interpret the results and conclude for the movietheater. You can read the case from the book.Regression EquationWeekly Gross Revenue ($1000s) 83.23 2.290 Televison Advertising ($1000s)+ 1.301 Newspaper Advertising ($1000s).CoefficientsTermCoef SE Coef T-Value P-Value VIFConstant83.231.5752.880.0007.530.001 1.45Televison Advertising ($1000s) 2.290Newspaper Advertising ($1000s) 1.3014.060.010 1.45Model SummaryS R-sq R-sq(adj) R-sq(pred)68. 19%0.642587 91.90% 88.66%Analysis of Variance+SourceRegressionTelevison Advertising ($1000s)Newspaper Advertising ($1000s)ErrorTotal0.3040.321DF Adj SS Adj MS F-Value P-Value2 23.435 11.717728.381 23.425 23.4247 56.731 6. 795 6.795316.465 2.065 0.4129725.500+0.0020.0010.010+K

The multiple linear regression model shows a relationship between 1 dependent variable and more than…

Answered: Question 4. Regression Analysis: Weekly…

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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Please no written by hand solutions 3. A researcher is interested in the correlation between a person’s age and the amount of sleep they get. He uses a poll to collect representative data for 2,000 people. The researcher performs a regression, with a dependent variable of minutes per week spent sleeping, and an independent variable of age in years. The regression results are as follows: - (Intercept): 150 - age: -5 Answer the following: - What is the regression line? - What is the predicted number of minutes sleeping for someone who is 20 years old? - The researcher is also interested in the relationship between age, sleep, and politics. Each person who responds to the poll chooses a value for liberal between 0 (very conservative) and 100 (very liberal) to describe their politics. The researcher performs a regression with the same independent variable of minutes per week sleeping, and dependent variables of age and liberal. The regression results are as follows: - (Intercept):…
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What is the dollar amount of change in sales for each new year according to the regression (slope) model? Do not use commas or $ in your answer.
The estimated regression model is given : Consumption = 49.13 + 0.85 Income + error Consumption is dependent variable ; Income ( weekly) - family Income Let's say a family income earns $ 100 more per week . How to affect the consumption level? Choose one right answer A. For every 100 $ a family earns more per week in this case the consumption will grow on average and expected of 85 $ worth. B. For every 100 $ a family earns more per week in this case the consumption will fall on average and expected of 49.14 $ worth.
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Prices and mileage of 48 Dodge 2500 Pickup trucks with Cummins diesel engines. Prices ranged from $28,925 to $68,650. Mileage ranged from 315 to 186,466. While I did not share the trucks were 2013 to 2020 models. Please show all work. Interpret b0 in the context of this problem. Interpret b1 in the context of this problem. What percent of total variation in prices is explained by the regression model? Provide evidence to support your answer. Price Mileage 52293 34450 50987 23372 62988 21738 37500 81176 66000 23118 47601 71143 47750 18214 42000 32303 50987 23372 28925 143737 42050 58561 51738 9691 51500 23969 44988 48781 29500 114809 46975 16918 63999 15507 46975 16918 43222 50459 38386 87192 42000 68722 62250 14042 62998 21738 32130 103644 52293 34450 52900 68883 53172 3656 53494 315 39594 88441 63246 23631 58250 34974 59391 18383 50650 42737 54976 84200 68650 14401 51114 47433 43900 74106 37450…
We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed. wage = -3.07 + 1.52 educ Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1
Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 1.5.
Explain how to find se
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