The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= -0.983. The least-squares regressionline treating weight as the explanatory variable and miles per gallon as the response variable is y = -0.0075x+46.5061. Complete parts (a) through (c) below.E Click the icon to view the data table.(a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon?The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %.(Round to one decimal place as needed.)(b) Construct a residual plot to verify the requirements of the least-squares regression model. Choose the correct graph below.OA.В.OC.O D.AResidual2-AResidual2-AResidual2-AResidual28-0-0-22--2-250040003250Weight (pounds)-2-250016-2500250032504000Weight (pounds)400032504000Weight (pounds)3250Weight (pounds)(c) Interpret the coefficient of determination and comment on the adequacy of the linear model.Question Viewer% of the variance inisby the linearodel. The least-squares regression model appears to bebased on the residual plot.(Round to one decimal place as needed.)Data tableFull data setWeight(pounds), xMiles perWeight(pounds), xCarCarMiles perGallon, yGallon, yCar 13,76518Car 72,60526StatcrunchCar 23,98417Car 83,77217Car 33,53021Car 93,31021Car 43,17523Car 102,99125Car 52,58027Car 112,75226Car 63,73018

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Answered: The accompanying data represent the…

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 shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 In the ANOVA F test output, what is the computed F and the conclusion of the test regarding the overall significance of the model?
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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 45 inches. Is the result close to the actual weight of 333 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 47 61 51 47 54 56 282 495 371 349 421 389 (...) What is the regression equation? y=+x (Round to one decimal place as needed.) an example Get more help. Clear all Check answer brrec Us |
Roller coasters get their speed as a result of dropping down a steep incline. The table below gives height of a drop and the speed achieved for different roller coasters around the world. Drop in Meters (m 25 30 28 58 55 40 90 100 Speed of the coaster (k.p.h) 80 90 78 93 90 93 105 128 Have your calculator find the linear regression for the roller coaster data above. Write the linear model, clearly define the variables and state correlation coefficient and clearly interpret the slope. Use the model to find the drop height that will result in a coaster speed of 150 kph. Have your calculator find the exponential regression for this data. Write the exponential model, clearly define the variables and state correlation coefficient. Use the model to find the drop height that will result in a…
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Is there a relationship between the weight and price of a mountain bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the bike's price. Weight (LB) 32 33 29 29 34 37 28 30 34 30 Price ($) 980 350 430 710 930 160 590 530 180 1090 a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the y-intercept have contextual meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the bike? a. Which scatterplot below correctly shows the data? A. 254001200xy A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…
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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.)
find t reject or fail to reject

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