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
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + OBedroom + yHouse Size + ALot Size Coef SE Coef Predictor T Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 R-Sq=56.0% R-Sq (adj)=54.6% S= 25023 Source DF MS F P Regression 3 76501718347 25500572782 *** **** Residual Error 96 60109046053 626135896 Total 99 a) Write out the regression equation. b) Fill in the missing values *, **, c) Use the p-value approach to determine if ø is significant at the 5% significance level and d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term "R-sq" and comment…
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…
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 groes f to budget is $100 million. Use a significance level of a 0.05. Budget (S)in Millions Gross (S) in Millions 45 17 114 67 70 49 117 67 3. 62 128 21 11 152 10 103 72 131 121 105 105 51 95 203 24 13 289 48 114 12 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y= x (Round to one decimal place as needed.)
estion 7 of 15 Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is y = -114.05 +2.17x. On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ŷ, when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bags Using the predicted value you just found, compute the residual at this temperature. residual = ice bags DOLL
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…
A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, v. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. A Click the icon to view the children's data. (a) Find the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. y=x+ (D (Round the slope to three decimal places and round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. First interpret the slope. Select the correct choice below and, if necessary. in the answer box to complete your choice. O A. For every inch increase in height, the head circumference increases by (Round to three decimal places as needed.) in., on average. O B. For a height of 0 inches, the head circumference is predicted to be (Round to three decimal places as…
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

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