We have data from 209 publicly traded companies (circa 2010) indicating sales and compensationinformation at the firm-level. We are interested in predicting a company's sales based on the CEO'ssalary. The variable sales; represents firm i's annual sales in millions of dollars. The variablesalary; represents the salary of a firm i's CEO in thousands of dollars. We use least-squares toestimate the linear regressionsales; = a + ßsalary; + eiand get the following regression results:. regress sales salarySourceModelResidualTotalsalessalaryconsSS3379204052.3180e+102.3518e+10df1207208Coef. Std. Err..9287785 .53465745733.917 1002.477MS337920405111980203113066454Number of obsF (1, 207)Prob > FR-squaredt P>|t|=Adj R-squared =Root MSE1.74 0.0845.72 0.000==-.12529343757.543=2093.020.08380.01440.009610582[95% Conf. Interval]1.982857710.291This output tells us the regression line equation is sales = 5,733.917 +0.9287785 salary.Interpret the numerical value of the regression slopein words that conveys the relationship between thevariables sales and salary.

Given, The regression equation of sales is, sales = 5,733.917 + 0.9287785×salaryWhere Salary is the…

Answered: We have data from 209 publicly traded…

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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The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Interpret the slope.
Compute the least-squares regression line for predicting the price of milk from the price of eggs. Round the slope and -intercept to at least four decimal places.
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y = sales price (in thousands of dollars) x₁ = total floor area (in square feet) x₂ = number of bedrooms x3 distance to nearest high school (in miles) = The estimated model is as follows. =76+0.098x₁ +16x₂ - 8x3 Answer the questions below for the interpretation of the coefficient of X₂ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each additional bedroom in a house? dollars (b) Is this change an increase or a decrease? O increase O decrease X
Please help with unanswered questions. Thank you!
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?
Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) PICK THE CORRECT ANSWER [A] We can be 98% confident that when the average weekly wages of state government employees is $878, the average weekly wages of…
The applet displays a scatterplot with the following points: (7,10),(27,35),(24,25),(8,12),(10,19),(15,22). Identify the slope of the regression line, intercept of the regression line, and correlation coefficient. Report your answers accurate to within two decimal places.
Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 64?
The slope of a regression line tells you how much or little a change in your dependent variable impacts your independent variable. O TrueO False
Pls help ASAP. Pls show all work.
What are the interpretations of the Y intercept and the slopes in a multiple regression model?

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