An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon.CarABDE DWeight (pounds), xMiles per Gallon, y2630 3095 3305 3655 415025.7 24.5222215.4O It is below average.O It is above average.(d) Draw the least-squares regression line on the scatter diagram of the data and label the residualWhich of the following represents the data with the residual shown in red?O A.OB.Oc.OD.4300-4300-2727-142500142500142500430014250027430027MPGMPGWeightWeightSign outhpsc$%&%238974.2 An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon.CarCEWeight (pounds), xMiles per Gallon, y2630 3095 3305 3655 415025.7 24.5222215.4M .. v v.The residual is miles per gallon.(Round to two decimal places as needed.)Is the value above or below average?It is below average.It is above average.(d) Draw the least-squares regression line on the scatter diagram of the data and label the residual.Which of the following represents the data with the residual shown in red?OC.OB.OA.

Value of x and y given We have to calculate regression equation by least square and graph for it.

Answered: An engineer wants to determine how 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 lists the birth weights (in pounds), x, and the lengths (in inches), y, for a set of newborn babies at a local hospital. Birth Weight (in Pounds), x Answer Length (in Inches), y Birth Weights and Lengths 10 7 21 18 7 4 12 7 10 3 1 17 12 12 16 21 19 22 15 21 20 Copy Data Step 2 of 2: Predict the length of an 8-pound baby. Assume the regression equation is appropriate for prediction. Round your answer to two decimal places necessary. Tables Keyboard S
An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B C D E Weight (pounds), x 2725 2875 3270 3715 4135 Miles per Gallon, y 27.4 23.3 22.9 20.5 18.7 (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. Write the equation for the least-squares regression line. y=__ x+__ (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)
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 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage. v. The une ory tor ine most recent m odel year. Complete parts (a) through (d) accompanying data represent the weights of various domestic cars and their miles per gallon in BEE Click here to view the weight and gas mileage data (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y = 0.00702 * + (43.2) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice.answer trom part a to find this answer O A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on averag B. For every pound added to the weight of the car, gas…
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B D E Weight (pounds), x Miles per Gallon, y 2545 3070 3375 3805 4250 24 32.6 24.5 24.6 18.2 (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. Write the equation for the least-squares regression line. (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and intercept, if appropriate. Choose the best interpretation for the slope. O A. The slope indicates the mean change in miles per gallon for an increase of 1 pound in weight. O B. The slope indicates the mean miles per gallon. O C. The slope indicates the ratio between the mean weight and the mean miles per gallon. O D. The slope indicates the mean weight. O E. It is not appropriate to interpret the…
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. D E Car Weight (pounds), x Miles per Gallon, y B 2570 2895 3455 3695 4235 23.5 24.4 20.5 17.6 DUBI (c) Predict the miles per gallon of car C and compute the residual. Is the miles per gallon of this car above average or below average for cars of this weight? The predicted value is miles per gallon. (Round to two decimal places as needed.) The residual is miles per gallon. (Round to two decimal places as needed.) Is the value above or below average? O It is below average. It is above average. # 14 M hp SC We.. among O G K S 7 C C BE ✓ S ✔ Time Rer
19. You might think that increasing the resources available would elevate the number of plant spe- cies that an area could support, but the evidence suggests otherwise. The data in the accompany- ing table are from the Park Grass Experiment at Rothamsted Experimental Station in the U.K., where grassland field plots have been fertilized annually for the past 150 years (collated by Harpole and Tilman 2007). The number of plant species recorded in 10 plots is given in response to the number of different nutrient types added Plot 1 2 3 4 5 6 7 8 9 10 Number of nutrients added 0 0 0 3144 E2 3 Number of plant species 36 36 32 34 33 30 20 23 21 16
In baseball, two statistics, the ERA (Earned Run Average) and the WHIP (Walks and Hits per Inning Pitched), are used to measure the quality of pitchers. For both measures, smaller values indicate higher quality. The following computer output gives the results from predicting ERA by using WHIP in a least-squares regression for the 2017 baseball season. Variable DF Estimate SE T Intercept 1 -5.0 0.26 - 19.3 WHIP 1 6.8 0.14 47.4 Which of the following statements is the best interpretation of the value 6.8 shown in the output? ERA is predicted to increase by 6.8 units for each 1 unit increase of WHIP. WHIP is predicted to increase by 6.8 units for each 1 unit increase of ERA. For a pitcher with 0 units of WHIP, the ERA is predicted to be approximately 6.8 units. For a pitcher with 0 units of ERA, the WHIP is predicted to be approximately 6.8 units. Approximately 6.8% of the variability in ERA is due to its linear relationship with WHIP.
The following table number of absences (x) and the grade earned on the first exam (y) for a Statistics class. 3. 9. 5 8. y 86 76 91 54 84 54 The least-squares regression line is in the form y= bo + b,x. Compute the value of bo. That is, compute the intercept. Round your answer to two decimal places. Write only a number as your answer. Your Answer: Answer
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 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)

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