The following data relate to the scores obtained by 9 salesmen of a company in an intelligence testand their weekly sales in thousand dollar:(a) Obtain the regression equation of sales on intelligence test scores of the salesman(b) If the intelligence test score of a salesman is 65, what would be his expected weekly sales?Salesmen Intelligence ATest Scores.Weekly Sales :503060505030H408070505080606070604060

Answered: Image /qna-images/answer/e1fa66e7-4957-4ebd-bbf5-3686c1e1c044.jpg

Answered: The following data relate to the scores…

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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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $120 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 40 20 118 67 71 48 119 62 8. 64 128 18 11 147 4 O 115 21 112 67 120 119 93 102 51 114 219 34 11 287 43 Click the icon to view the critical values of the Pearson correlation coefficient r. В... The regression equation is y =+x. (Round to one decimal place as needed.)
The numbers of pass attempts and passing yards for seven professional quarterback for a recent year are listed in the table below. Round all answers to the nearest 1000th. Pass attempts (x) 449 565 528 197 670 351 218 Passing Yards (y) 3265 4018 3669 1141 5177 2362 1737 Calculate the sample correlation coefficient, r. Describe the type of correlation coefficient and interpret the correlation in the context of the data. Find the equation of the regression line for the data. Use the regression equation to predict the average number passing yards if the pass attempts are 250.
Consider the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 6.5 10 11 12.5 13 14.5 15 17.5 19.5 20 Grade y 66.1 63 71.4 72.5 79.2 94.3 95 91.5 100 98 The regression equation is y = 3x + 41.3. a) Explain what the value of the slope means in this situation, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. O For each additional hour per week that a student studies on average, their final grade will be about 3 points. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points higher. For each additional hour per week that a student studies on average, their final grade will be about 3 points higher. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points. b) Explain what the value of the…
An institutional research administrator believes that there is a direct relationship between a student’s GPA and their score on a senior Aptitude Test. The following data show the results of 10 student’s grade point averages (X) and their aptitude test score (Y). GPA (X) Aptitude Test Score (Y) 2.4 25 2.5 32 2.6 28 2.4 37 3.1 33 3.0 38 3.7 44 3.4 42 3.8 49 Develop an estimated regression equation relating GPA and Aptitude Test score. Use the formulas from our notes to compute this equation. SHOW ALL WORK!! DO NOT USE EXCEL!! If a student’s GPA is 3.35, predict their Aptitude Test score
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The age and prices of 11 Nissan cars given in the following data: Age (in years) 5 4 6 5 5 5 6 6 2 7 7 Price (in $100s) 85 103 70 82 89 98 66 95 169 70 48 a. Obtain the correlation coefficient between the age and price of the cars. Interpret the value of the correlation coefficient. b. Obtain a regression equation of Price (dependent variable) on Age (Independent variable). c. What will be the Price of the car after 3 years? d. Find the coefficient of determination. Determine the percent of variation that is explained by the regression equation clearly.
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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)

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