A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where total = 40.+63.70xANOVARegressionResidualTotalInterceptNumber ofSalespersonswe rejectdfCoefficients76.043.0a. Write the estimated regression equation (to whole number).ŷ =✔7643b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)t Statp-value is less than 0.01Ho ₁ 0.0001d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons.$thousand (to whole number)SS6,404.58,931.6F-valuep-value is less than 0.01we rejectНоc. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)10.25 XMS F×Standard Error10.4835.506Significance Ft StatP-value

a.The regression analysis for the number of sales person (x) and the annual sales (y) is given.The…

Answered: A regression model relating , number of…

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 following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777
10) A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
From a regression equation r2= 0.39 and the slope = -2.8 What is the linear correlation coefficient r?
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 78 63 85 92 82 89 69 89 83 61 Grades on Final 77 75 88 92 86 86 80 85 77 63
**Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the predicted value of income for a person that has been in a house for 5 years, is 38 years old, is a male, has a house valued at $250,000, and has $100,000 left on their mortgage? (g) What is the effect on the income of a person being a male versus a female?
A regression modrel examining the amount of distance a long-ddistance runner runs (in miles) to predict the amount of fluid the runner drinks (ounces0 has a slope of 4.6. Which interpretation is appropiate? The correlation is needed to interpret this value. Arunner drinks minimum of 4.6 oz. We predict 4.6 miles for every ounce that drunk. We predict for every mile run, the runner drinks 4.6 more ounces. Each mile adds 4.6 more ounces.
Increase in sales (percent) An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to be y = 6.16+0.18x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.) Increase in sales, y Campaign cost, x (in millions of dollars) (percent) 3.02 6.91 7.2+ 1.92 6.80 3.83 6.85 6.8- 1.40 6.37 6.6 - 3.12 6.42 3.56 6.82 6.4- 4.06 6.94 6.2 1.64 6.56 6- 2.06 6.50 1.62 6.18 1.5 2.5 3.5 6.66 Campaign cost (in millions of dollars) 2.87 2.25 6.61 Send data to calculator Based on the firm's data and the regression line, complete the following. (a)…
The regression line for the given data is = 6.91x + 46.26. Determine the residual of a data point for which x = 4 and y = 75.
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.853 b=34.041 r2=0.389376 r=-0.624 Use this to predict the number of situps a person who watches 7 hour(s) of TV can do, and please round your answer to a whole number.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right am blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 100 mm Hg Use a significance level of 0.05. Right Arm 103 102 95 78 Left Arm 175 169 147 146 144 m Click the icon to view the critical values of the Pearson correlation coetticient r The regression oquation is y =+O (Round to one decimal place as needed) Given that the systolic blood pressure in the right arm is 100 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg (Round to one decimal place as needed.)
I was wondering specifically about part D and how to interpret my findings.
A regression was run to determine if there is a relationship between hours of study per week (�) and the test scores (�).The results of the regression were:y=ax+b a=6.254 b=33.41 r2=0.976144 r=0.988 Use this to predict the final exam score of a student who studies 3 hours per week, and please round your answer to a whole number.

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