The regression equation is intended to be the best fitting straght line for a set of data. What is the criterionfor "best fitting"?a. A line that touches all of the data points.b. A line that results in the least squared error between the data points and the line.c. A line that predicts where every X value is in the data set.d. None of the above.

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Answered: The regression equation is intended to…

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 grades of 7 students in the midterm and final grading period are shown in the table. Find the equation of the regression line. 80 78 76 82 84 85 75 y 84 79 75 86 84 77 78 y = 40.2x + 0.5x y = 40.29 0.5x O XXXW O wxwx y = 40.29 + 0.5x XXXX XXWX y = 40.29x + 0.5
Read the following description of a data set. The owner of a bicycle store wonders if the employees who take the longest lunch breaks also make the fewest bicycle sales. One day, she notes the length of each salesperson's lunch break (in minutes), x, as well as the number of bicycles he or she sold that day, y. The least squares regression line of this data set is: ŷ = -0.297x + 10.889 Complete the following sentence: If a salesperson spends one additional minute at lunch, the least squares regression line predicts he or she will sell | fewer bicycles that day. Submit е
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
B. What is the equation of the regression line for the set of 9 points? y=___ C. Choose the correct description of the results below. The removal of the point has a significant impact on the regression line. There is no regression line for the second case because the data are in a pattern. The regression line is very similar in both cases. The regression line changes, but the change is small.
2
A. Write the equation of the regression line. B. Interpret each one of the slopes in this context. C. Calculate the estimated number of days absent and the residual for the first observation in the data set: a student who is aboriginal, male, a slow learner, and missed 2 days of school.
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y Un ne conteui yrapii veIUW. O A. Stories A 60- Height (feet) OO ( 800 (a) Predict the value of y for x = 503. Choose the correct answer below. A. 40 OB. 47 O C. 50 O D. not meaningful (b) Predict the value of y for x = 652. Choose the correct answer below. 774 51 OA. 54 O B. 47 OC. 40 O D. not meaningful (c) Predict the value of y for x = 810. Choose the correct answer below. OA. 54 625 47 OA. 54 OB. 50 OC. 47 O D. not meaningful (d) Predict the value of y for x = 725. Choose the correct answer below. B. 40 ΕΛ 521 45 O B. Stories 60+ 508 41 0 Height (feet) 800 497 38 477…
The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 5.1 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 101 8 8 3 12 12 8 5.5 7.4 6.8 4.7 5.6 6.6 2.3 9.1 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 5.1 million? O A. The result is exactly the same as the actual number of viewers of 5.1 million. O B.…
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A random sample of ten professional athletes produced the following data. The first row is the number of endorsements the athlete has and the second row is the amount of money made (in millions of dollars) by the athlete.   What is the slope of the line of best fit? Round to 3 decimal places. Number of Endorsements 0 3 2 1 5 5 4 3 0 4 Profit (in Millions) 2 8 7 3 13 12 9 9 3 10
Which of the following statements is true? 1. The R (ie., R-squared) tells us the percentage of the variation in the dependent variable (cost) that is explained by variation in the independent variable (activity) II The R (e. R-squared) varies from 0% to 100%, and the lower the percentage, the better the fit of the data to a straight line. ONeither statement is true. Only statement I is true. Only statement II is tru. Both statements are true.

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