Question 2In Exercises 14.38 through 14.43, we give the total variation, the unexplained variation (SSE), and theleast squares point estimate b, that are obtained when simple linear regression is used to analyze the dataset related to each of six previously discussed case studies. Using the information given in each exercise,find the explained variation, the simple coefficient of determination (r²), and the simple correlationcoefficient (r). Interpret r².14.38 THE NATURAL GAS CONSUMPTION CASE DS GasCon1Total variation = 25.549; SSE = 2.568; b₁ = .1279214.39 THE STARTING SALARY CASE DS StartSalTotal variation = 61.380; SSE = 1.438; b₁ = 5.706614.40 THE SERVICE TIME CASE OS SrvcTimeTotal variation = 20,110.5455; SSE = 191.7017; b₁ = 24.602214.41THE FRESH DETERGENT CASE OS FreshTotal variation = 13.459; SSE = 2.806; b₁ = 2.665214.42 THE DIRECT LABOR COST CASE DS DirLabTotal variation = 1,025,339.6667; SSE = 746.7624; b₁ = 10.146314.43 THE REAL ESTATE SALES PRICE CASE DS RealEstTotal variation = 7447.5; SSE = 896.8; b₁ = 5.7003

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Answered: Question 2 In Exercises 14.38 through…

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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A company wishes to estimate a regression line for the relationship between sales and advertising. а. To arrive at its decision regarding the best model to use, the company has calculated the following three correlation coefficients. i. ii. The sales in any month depend on that month's advertising with r = 0.28 The sales in any month depend on 50% of the previous month's advertising and 50% of that month's advertising with r= 0.68 The sales in any month depend on the previous month's advertising with r = 0.92 iii. Interpret each of the above correlation coefficients and state which of the suggested models you would choose as the basis for predicting sales. Justify your answer.
Data from 10 Western European countries: summary statistics show that the mean percent of teens that use marijuana is 23.9 with a standard deviation of 15.6. The mean percent of teens that use other drugs is 11.6 with a standard deviation of 10.2. The correlation coefficient is r= 0.93 Find the equation of the least squares regression line considering Marijuana Use as the Explanatory variable and Other Drug Use as the Response variable. O a. ý = 7.43 + 1.42x O b. ý = - 1.42 -0.61x %3D Oc = -2.98 +0.61x %3D O d. ý = 6.10 +2.98x
Please give answers of b&c
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A movie studio wishes to determine the relationship between the revenue from the streaming rental of comedies and the revenue generated from the theatrical release of such comedies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming rentals (in millions of dollars) for each of the fifteen movies. The data are displayed in the Figure 1 scatter plot. Also given is the product of the theater revenue and the rental revenue for each of the fifteen movies. (These products, written in the column labelled "xy", may aid in calculations.) Theater Rental revenue, y revenue, x xy (in millions of (in millions of dollars) dollars) 61.7 9.7 598.49 15.1 1.7 25.67 45.3 6.3 285.39 28.1 12.1 340.01 49.1 16.1 790.51 xx 12.9 10.2 131.58 28.1 2.4 67.44 66.0 9.7 640.2 20.6 5.8 119.48 7.5 2.8 21 25.8 6.9 178.02 Theater revenue 36.2 12.8…
Given the following data set, let x be the explanatory variable and y be the response variable. x75 1 8812 y36102398 (a) If a least squares line was fitted to this data, what percentage of the variation in the y would be explained by the regression line? (Enter your answer as a percent.) ANSWER: % (b) Compute the correlation coefficient: r =
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