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= - 0.984. The least-squares regressionline treating weight as the explanatory variable and miles per gallon as the response variable is y = - 0.0066x + 43.3954. Complete parts (a) and (b) below.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?Data TableThe 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) Interpret the coefficient of determination.Full data set% of the variance inisby the linear model.Miles perMiles perWeight(pounds), xWeight(pounds), xCarCar(Round to one decimal place as needed.)Gallon, yGallon, yCar 13,76519Car 72,60526Car 23,98418Car 83,77218Car 33,53021Car 93,31021Car 43,17523Car 102,99124Car 52,58027Car 112,75225Car 63,73018

Answer:----. Date:----12/10/2021 r = -0.984 So, r^2 = 0.968256

Answered: per ge The proportion of 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 amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). C (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? A. The variable "weekly time spent watching television" is likely skewed right, not normally distributed. OB. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. O C. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. O D. The variable "weekly time spent watching television" is likely normally distributed. O E. The variable "weekly time spent watching television" likely uniform, not normally distributed. (b) According to a certain survey, adults spend 2.45 hours per day watching television on a weekday. Assume that the standard deviation for "time…
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What is the interpretation of the intercept regression coefficient in a regression model? A. The change in X for a unit increase of Y B. The change in Y for a unit increase of X C. The estimated value of the dependent variable when X takes the value 1 D. The estimated value of the dependent variable when X takes the value 0
:0 F1 @ 2 F2 W S For major league baseball teams, is there a relationship between player payrolls and gate money? Here are data for each of the National League teams for the year 2002. The variable x denotes the 2002 player payroll (in millions of dollars), and the variable y denotes the mean attendance (in thousands of fans) for the team's home games that year. The data are plotted in the Figure 1 scatter plot. Arizona Atlanta Chicago Cubs Cincinnati Colorado Florida Houston Los Angeles Milwaukee Montreal New York Mets Philadelphia Pittsburgh San Diego San Francisco St Louis Send data to calc.... Check Mean Player payroll, x attendance, (in $1,000,000 s) #3 80 F3 103.5 93.8 E ✓ D 75.0 46.3 56.6 40.8 65.4 101.5 49.3 37.9 94.4 59.6 46.1 41.8 78.4 76.2 $ 4 The least-squares regression line for these data has a slope of approximately 0.34. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary,…
Which of the slopes matches best with the slope of the data in the scatter plot? would it be m = 3/8?, m = 8/3?, m = - 3/8? or would it be m = - 8/3???
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The scatter plot shows the relationship between the number of minutes studying for a test (x) and the Score earned (y). Make a scatterplot for the data. Time Studying (x) 40 50 60 70 80 90 100 110 Score (y) 2 3 6 7 9. +H+ 10 6. -7- 4 3 1- 10, 10 20 30 40 50 60 70 80 90 100 110 12 7:04 PM Desktop 12/8/2026
ea surface temperature26.726.726.626.626.626.626.526.526.326.326.126.1Growth0.850.850.850.850.790.790.860.860.890.890.920.92 Make a scatterplot. Which is the explanatory variable? The plot shows a negative linear pattern. Explanatory Variable:
The following table shows the values of the age and the job satisfaction of ice cream shop employees Employee Age Job Satisfaction16 918 920 722 824 426 528 626 524 722 8 d. Sketch a scatterplot of this data by hand (do NOT use/submit any plots created by a program).e. Does there appear to be a linear relationship between the two variables? f. Calculate the slope for this data.

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