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 regression line treating weight as the explanatory variable and miles per gallon as the response variable is \( \hat{y} = -0.0066x + 43.3954 \). Complete parts (a) and (b) below.(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 \(\square\)%.(Round to one decimal place as needed.)(b) Interpret the coefficient of determination.\(\square\%\) of the variance in \(\square\) is \(\square\) by the linear model.(Round to one decimal place as needed.)**Data Table**| Car | Weight (pounds), \( x \) | Miles per Gallon, \( y \) ||-------|--------------------------|---------------------------|| Car 1 | 3,765 | 19 || Car 2 | 3,984 | 18 || Car 3 | 3,530 | 21 || Car 4 | 3,175 | 23 || Car 5 | 2,580 | 27 || Car 6 | 3,730 | 18 || Car 7 | 2,605 | 26 || Car 8 | 3,772 | 18 || Car 9 | 3,310 | 21 || Car 10| 2,991 | 24 || Car 11| 2,752 | 25 |**Note:**- The correlation coefficient \( r = -0.984 \) indicates a strong negative linear relationship between the weight of the car and the miles per gallon.- The least-squares regression line equation is given as \( \hat{y} = -0.0066x + 43.3954 \), where \( \hat{y} \) is the predicted miles per gallon and \( x \) is the car’s

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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Suppose trips/wk =3.1 -0.15(dist) is a linear model that predicts the number of supermarket trips a family makes per week when they live a certain distance (in miles) from a supermarket. It was established by sampling people who live within 10 miles of a supermarket. Which of the following is the correct interpretation of the slope? O a. For each additional trip that the family makes, they live 0.15 miles away from the store O b. For each additional mile away from the store the family lives, they make 0.15 more visits per week O. For each additional mile away from the store the family lives, they make 0.15 fewer visits per week O d. For each additional trip they make to the store, they live an additional 3.1 miles away. O e. For each additional mile away they live, they make 3.1 more trips to the stor.
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Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent The distance from point of release to point of recovery in km/100. The following data a representative of one study using drift bottles to study ocean currents. x day 72 79 32 96 203 y km/100 14.8 19.6 5.3 11.8 35.1 Σx=482 Σy=86.6 Σx2=62874 Σy2=2002.54 Σxy=11041.7 r=.93787 use a 1% level of significance to test the claim p>0.(use 2 decimal places) t=critical t= Se=4.4913 a=1.4966 b=.1641 D) find the predicted distance (km/100) when a drift bottle has been floating for 80 days.(use 2 decimal places) find a 90% confidence interval for your prediction of part D. (use 2 decimal places) lower limit=___km/100upper limit=___km/100 he was a 1% level of…

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