b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?There appears to be al- Select your answer -Select your answer|linear relationship between a and y.e and y by drawing a straight line through the data.c. Try to approximate negativepositive- Select your answer -vto provide a linear approximation of the relationship between a and y.d. Develop the estimated regression equation by computing the values of bo and bi using equations: (Enter negative values as negative figure)(t; – F)(yi – ỹ)-bịbo = j – bịax (to 2 decimals)e. Use the estimated regression equation to predict the value of y when x = 6.(to 2 decimals)b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?There appears to be a - Select your answer -linear relationship between a and y.c. Try to approximate the relationship between a and y by drawing a straight line through the data.to provide a linear approximation of the relationship between a and y.n by computing the values of bo and bị using equations: (Enter negative values as negative figure)- Select your answer -Select your answerMany different straight lines can be drawnOnly one straight line can be drawnA straight line cannot be drawn\Yi - Y)bo = j – ba=+x (to 2 decimals)e. Use the estimated regression equation to predict the value of y when a = 6.(to 2 decimals)|| Given are five observations for two variables, x and y.4 10 9 23 14Y 56 49 52 10 28a. Choose the correct scatter diagram for these data:A.В.y!60-60-50-5040-40-30-3020-20-10+10-102030405060 x102030405060 xD.60-60-505040-40-30+30-2020-10-10-102030405060 x102030405060 xb. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?There appears to be a - Select your answer -linear relationship between z and y.vc. Try to approximate the relationship between z and y by drawing a straight line through the data.|- Select your answer -v to provide a linear approximation of the relationship between æ and y.d. Develop the estimated regression equation by computing the values of bo and bị using equations: (Enter negative values as negative figure)b =bo = j - bịa+1a (to 2 decimals)e. Use the estimated regression equation to predict the value of y when z = 6.=(to 2 decimals)

The data shows x and y variables with five observations.

Answered: Given are five observations for two…

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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1. Consider the following table of data: Defects per 100 vehicles (alphabetical by brand) BRAND. DEFECTS Acura. 89 Audi. 111 BMW. 113 Buick. 114 Cadillac. 111 Chevrolet. 111 Chrysler. 126 Dodge. 131 Ford. 104 GMC. 124 Honda. 88 Hyundai 80 Infinite. 83 Jaguar. 129 Jeep. 128 Kia. 135 Land Rover 175 Lexus. 107 Lincoln. 93 Mazda. 114 Mercedes-Benz 106 Mercury. 113 MINI. 125 Mitsubishi. 147 Nissan. 111 Porsche. 91 Ram. 110 Scion. 114 Subaru. 130 Toyota. 117 Volkswagen. 132 Volvo. 96 A. Construct a stem-and-leaf plot for the number of defects per 00 vehicles for these 32 brands. S-and-LP for. Weights Stem unit. =. 10 Leaf unit. =. 1 Frequency. S. L
14. The following table gives the miles per gallon and the load capacity for 6 SUV's. Miles per Gallons Load Сарacity 19 860 17 970 16 1035 16 1165 14 1180 13 1360 a. Develop a scatter diagram for the data. b. How would you characterize the relationship between miles per gallon and load capacity?
The following table lists highway miles (in MPG) and weight (in pounds) for a variety of cars, foreign and domestic (same data as before). CAR HWY WEIGHT Chev. Cavalier 31 2795 Lincoln Cont. 24 3930 Mitsubishi Eclipse 33 3235 Olds. Aurora 26 3995 Pontiac Grand Am 30 3115 Chev. Corvette 28 3220 BMW 3-Series 27 3225 Ford Crown Victoria 24 3985 Hyundai Accent If we let x be the weight and y be the Highway MPG, and we used Excel to compute the equation of the Least- 37 2290 Square regression line (which comes out to be y = -0.00672'x + 51.1156) as well as the correlation coefficient (which comes out to be -0.89). Then you used that equation to predict that the Highway Miles for a car that weighs just 1000 pounds would be 44.4 mpg. I think this prediction is accurate because the person used Excel for the computation. O I think this prediction is not accurate since a car that weighs 1000 pounds is not part of the original data list. O Ithink this prediction is not accurate because the person…
2) Let x represent the average annual hours per person spent in traffic delays and y represent the average annual gallons of fuel wasted per person in traffic delays. A random sample of 8 cities showed the following data: X Y 28 jo 48 5 12 3 20 34 35 ZD 25 20 34 23 30 35 40 38 18 a) Draw a scatter plot diagram and the line that you think that best fits the data 60%" so: Ave Gallons 40 30 28 5 Five. Hours Delay 9 b) Would you say the correlation is positive, negative or close to zero?
The following data are the numbers of local channels available in 16 citie 16, 10, 20, 8, 35, 20, 13, 28, 38, 31, 21, 27, 9, 11, 28, 27 Send data to calculator Using the tool provided, construct a box-and-whisker plot for the data. 10 15 20 25 30 35 40 Number of local channels avalable 5n
The following observations are for two quantitative variables, and y. Observation Observation 1 27 63 11 21 81 2 24 100 12 85 24 3 58 53 13 67 39 4 73 38 14 15 99 TITI 5 48 62 15 82 37 6 88 23 16 32 63 7 30 47 17 44 56 8 10 93 18 54 64 9 66 46 19 31 27 10 61 52 20 30 28 If your answer is "zero", enter "0". a. Develop a crosstabulation for the data, with as the row variable and y as the column variable. For use classes of 10 - 29, 30-49, and so on; for y use classes of 20 - 39, 40-59, and so on. y x 80-100 Grand Total 20 - 39 40 - 59 60 - 79 X X X 10-29 X X X X 30-49 X X X X X 50-69 X X X X 70 - 90 Grand Total b. Compute the row percentages (to 1 decimal). Y I 20 - 39 40-59 80 - 100 Grand Total X% 10-29 30-49 X% % % 50 - 69 X % *% 70-90 c. Compute the column percentages (to 1 decimal). Y 20 - 39 40 - 59 *% 10 - 29 % 30-49 50 - 69 70 - 90 Grand Total % 1% % % *% 60 - 79 % % 1% % ¹% X % % X. % % 60 - 79 X. % *% X% % % X% X % *% % 80-100 * % % % 1% X% % *% 1% %
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