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7. A study was performed on wear of a surface "y" and its relationship to x...
Problem 1: (7 pointsl A study was performed on wear of a bearing Y and its relationship to XI - oil viscosity and X2 load. The following data were obtained. Use the Minitab output on the next pag...
Problem 1: (7 pointsl A study was performed on wear of a bearing Y and its relationship to XI - oil viscosity and X2 load. The following data were obtained. Use the Minitab output on the next page to answer questions (a) to (e) XI 1.6 230 15.5 816 172 22.0 1058 293 91 113 125 43.0 1201 33.0 1357 40.0 1115 polnsl Find the regression equation that links the bearing Y to the oil viscosity and the load. )...
Question 8(Multiple Choice Worth 5 points) (02.05 MC) Regressions were performed on measurements, x and y,...
Question 8(Multiple Choice Worth 5 points) (02.05 MC) Regressions were performed on measurements, x and y, taken on 8 subjects. Regression 1 produced y = 57.1024 + 17.331x and had the residual plot: 30 25 20 15 10 . 5 0 0 2 4 6 8 10 12 14 16 -5 -10 -15 -20 Regression 2 produced vý = 0.158283 +0.98559 x and had the residual plot: 0.15 0.1 0.05 0 0 2 4 6 8 10 12 14 16...
A student was performed on a type of bearing to find the relationship of amount of...
A student was performed on a type of bearing to find the relationship of amount of wear y to X1 = oil viscosity and X2 = load. The accompanying data were obtained. Complete parts (a) and (b) below. Click here to view the bearing data. Click here to view page 1 of the table of critical values of the t-distribution. Click here to view page 2 of the table of critical values of the t-distribution. (a) Estimate o2 using multiple...
Twenty-one daily responses of stack loss (y) (the amount of ammonia escaping) were measured with air...
Twenty-one daily responses of stack loss (y) (the amount of ammonia escaping) were measured with air flow x1, temperature x2, and acid concentration x3. Obtain a matrix plot of scatter plots for all pairs of variables using Minitab, and state your conclusion based on this graph. [5 marks] Find a multiple linear regression model for this data using Minitab. [5 marks] Check the significance of the model using ANOVA via Minitab and state your conclusion at 5% alpha level. [5...
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 ...
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1
use second picture please A regression analysis was performed to determine if there is a relationship...
use
second picture please
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.326 b=30.621 p2=0.6561 r=-0.81 Use this to predict the number of sit ups a person who watches 14 hours of TV can do, and please round your answer to a whole number. The following is data for the...
Car Weight (pounds), x Miles per Gallon, y 1 3,765 19 2 3,984 18 3 3,530 ...
Car Weight (pounds),
x Miles per Gallon, y
1 3,765 19
2 3,984 18
3 3,530 20
4 3,175 22
5 2,580 26
6 3,730 18
7 2,605 25
8 3,772 18
9 3,310 20
10 2,991 24
11 2,752 25
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= -0.97 The...
Please use DataAnalysis A study was conducted to build a regression model to predict miles per gallon (MPG) of vehicles...
Please use DataAnalysis
A study was conducted to build a regression model to predict miles per gallon (MPG) of vehicles. To develop the model, you obtained MPG of 43 random vehicles. In addition, you collected the following information - Length: vehicle length (inches) - Width: vehicle width (inches) - Weight: vehicle weight (pounds) - Made in Japan: whether the car is manufactured in Japan or not a. Fit a multiple regression model using all four independent variables. For "made in...
Running a manufacturing operation efficiently requires knowledge of the time it takes employees to manufacture the...
Running a manufacturing operation efficiently requires knowledge of the time it takes employees to manufacture the product, otherwise the cost of making the product cannot be determined. Estimates of production time are frequently obtained using time studies. The data in the table below came from a recent time study of a sample of 15 employees performing a particular task on an automobile assembly line. Time to Assemble, y (minutes) Months of Experience, x 10 24 20 1 15 10 11...
Q6). We are interested in exploring the relationship between the weight of a vehicle and its...
Q6). We are interested in exploring the relationship between the weight of a vehicle and its fuel efficiency (gasoline mileage). The data in the table show the weights, in pounds, and fuel efficiency, measured in miles per gallon, for a sample of 12 vehicles. Weight Fuel Efficiency 2710 24 2550 24 2680 29 2720 38 3000 25 3410 22 3640 21 3700 27 3880 21 3900 19 4060 21 4710 16 Part (c) Find the equation of the best fit...
Problem 1: (7 pointsl A study was performed on wear of a bearing Y and its relationship to XI - oil viscosity and X2 load. The following data were obtained. Use the Minitab output on the next page to answer questions (a) to (e) XI 1.6 230 15.5 816 172 22.0 1058 293 91 113 125 43.0 1201 33.0 1357 40.0 1115 polnsl Find the regression equation that links the bearing Y to the oil viscosity and the load. )...
Question 8(Multiple Choice Worth 5 points) (02.05 MC) Regressions were performed on measurements, x and y, taken on 8 subjects. Regression 1 produced y = 57.1024 + 17.331x and had the residual plot: 30 25 20 15 10 . 5 0 0 2 4 6 8 10 12 14 16 -5 -10 -15 -20 Regression 2 produced vý = 0.158283 +0.98559 x and had the residual plot: 0.15 0.1 0.05 0 0 2 4 6 8 10 12 14 16...
A student was performed on a type of bearing to find the relationship of amount of wear y to X1 = oil viscosity and X2 = load. The accompanying data were obtained. Complete parts (a) and (b) below. Click here to view the bearing data. Click here to view page 1 of the table of critical values of the t-distribution. Click here to view page 2 of the table of critical values of the t-distribution. (a) Estimate o2 using multiple...
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1
use
second picture please
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.326 b=30.621 p2=0.6561 r=-0.81 Use this to predict the number of sit ups a person who watches 14 hours of TV can do, and please round your answer to a whole number. The following is data for the...
Car Weight (pounds),
x Miles per Gallon, y
1 3,765 19
2 3,984 18
3 3,530 20
4 3,175 22
5 2,580 26
6 3,730 18
7 2,605 25
8 3,772 18
9 3,310 20
10 2,991 24
11 2,752 25
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= -0.97 The...
Please use DataAnalysis
A study was conducted to build a regression model to predict miles per gallon (MPG) of vehicles. To develop the model, you obtained MPG of 43 random vehicles. In addition, you collected the following information - Length: vehicle length (inches) - Width: vehicle width (inches) - Weight: vehicle weight (pounds) - Made in Japan: whether the car is manufactured in Japan or not a. Fit a multiple regression model using all four independent variables. For "made in...
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