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A random sample of 30 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Assume the conditions for inference are met. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% S = 466.2 with 30 - 2 = 28 degrees of freedom Variable Constant Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 0.0106 P-value 0.0050 S0.0001 Sales Which of the following is an appropriate interpretation of the number 0.092498? For each increase of $100,000 in sales, the predicted profit increases by $9,249.80 O For each increase of $100,000 in profits, the predicted sales increases by $9,249.80 Sales of $100,000 correspond to predicted average profits of $9,249.80 The actual profit typically varies by about $9249.80 from the profit predicted with the least squares regression line using x = sales O The actual sales typically varies by about $9249.80 from the sales predicted with the least squares regression line using x = profit.

A random sample of 30 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Assume the conditions for inference are met. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% S = 466.2 with 30 - 2 = 28 degrees of freedom Variable Constant Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 0.0106 P-value 0.0050 S0.0001 Sales Which of the following is an appropriate interpretation of the number 0.092498? For each increase of $100,000 in sales, the predicted profit increases by $9,249.80 O For each increase of $100,000 in profits, the predicted sales increases by $9,249.80 Sales of $100,000 correspond to predicted average profits of $9,249.80 The actual profit typically varies by about $9249.80 from the profit predicted with the least squares regression line using x = sales O The actual sales typically varies by about $9249.80 from the sales predicted with the least squares regression line using x = profit.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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A random sample of 30 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Assume the conditions for inference are met. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% S = 466.2 with 30 - 2 = 28 degrees of freedom Variable Constant Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 P-value 0.0050 S0.0001 Sales 0.0106 Which of the following is an appropriate interpretation of the number 0.092498? For each increase of $100,000 in sales, the predicted profit increases by $9,249.80 For each increase of $100,000 in profits, the predicted sales increases by $9,249.80 Sales of $100,000 correspond to predicted average profits of $9,249.80 The actual profit typically yaries by about $9249.80 from the profit predicted with the least squares regression line using x = sales The actual sales typically varies by about $9249.80 from the sales predicted with the least squares regression line using x = profit.
Transcribed Image Text:A random sample of 30 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Assume the conditions for inference are met. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% S = 466.2 with 30 - 2 = 28 degrees of freedom Variable Constant Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 P-value 0.0050 S0.0001 Sales 0.0106 Which of the following is an appropriate interpretation of the number 0.092498? For each increase of $100,000 in sales, the predicted profit increases by $9,249.80 For each increase of $100,000 in profits, the predicted sales increases by $9,249.80 Sales of $100,000 correspond to predicted average profits of $9,249.80 The actual profit typically yaries by about $9249.80 from the profit predicted with the least squares regression line using x = sales The actual sales typically varies by about $9249.80 from the sales predicted with the least squares regression line using x = profit.
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