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You work for a large dairy farm and are examining the farm's techniques for rearing their Holstein calves. You want to see how large the farm's Holstein calves get as they age. So, you are going to take a random sample aof 11 of the calves and note the age of each calf (denoted by X, in months) and their weight (denated by y, in kg). You will also note the product X-y of the age and the weight for each of the calves. (These products are written in the row labeled "Xy"). (a) Click on "Take Sample" to see the results for your random sample. Calf age, X 3 11 6 9 1 5 11 (in months) Calf weight, Taku Sample 112 132 321 223 192 241 250 57 171 298 195 y (in lg) 336 660 3531 1561 1152 1928 2250 57 855 3278 1365 xy Sand data to calculator v Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three decimal placns. When you are done, select "Compute". (In the table below, A is the sample size and the symbol I xy means the sum of the values Xy.) Sample correlation coefficient (F): I: 0 Slope (): I xy: 0 y-intercept (): Compute (b) Write the equation of the least-squares regression line for your data. Then on the scatter plot for your data, graph this regression equation by plotting two points and then drawing the line through them. Round each coordinate to three decimal places. Regression equation: =0 Calf age (in months) (c) Use your regression equation to predict the weight of a 10-month-ald Holstein calf on the farm. Round your answer to the nearest whole number. Predicted weight: kilograms Calf weight

You work for a large dairy farm and are examining the farm's techniques for rearing their Holstein calves. You want to see how large the farm's Holstein calves get as they age. So, you are going to take a random sample aof 11 of the calves and note the age of each calf (denoted by X, in months) and their weight (denated by y, in kg). You will also note the product X-y of the age and the weight for each of the calves. (These products are written in the row labeled "Xy"). (a) Click on "Take Sample" to see the results for your random sample. Calf age, X 3 11 6 9 1 5 11 (in months) Calf weight, Taku Sample 112 132 321 223 192 241 250 57 171 298 195 y (in lg) 336 660 3531 1561 1152 1928 2250 57 855 3278 1365 xy Sand data to calculator v Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three decimal placns. When you are done, select "Compute". (In the table below, A is the sample size and the symbol I xy means the sum of the values Xy.) Sample correlation coefficient (F): I: 0 Slope (): I xy: 0 y-intercept (): Compute (b) Write the equation of the least-squares regression line for your data. Then on the scatter plot for your data, graph this regression equation by plotting two points and then drawing the line through them. Round each coordinate to three decimal places. Regression equation: =0 Calf age (in months) (c) Use your regression equation to predict the weight of a 10-month-ald Holstein calf on the farm. Round your answer to the nearest whole number. Predicted weight: kilograms Calf weight

MATLAB: An Introduction with Applications
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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You work for a large dairy farm and are examining the farm's techniques for rearing their Holstein calves. You want to see how large the farm's Holstein calves get as they age. So, you are going to take a random sample af 11 of the calves and note the age of each calf (denoted by X, in months) and their weight (denated by y, in ke). You will also note the product X-y of the age and the weight for each of the calves. (These products are written in the row labeled "Xy"). (a) Click an "Take Sample" to see the results for your random sample. Calf age, X 3 11 7 6 1 5 11 7 (In months) Calf welght, Tako Samplo 112 132 321 223 192 241 250 57 171 298 195 (In lg) xy 336 660 3531 1561 1152 1928 2250 855 3278 1365 Sand data to calculator v Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three dedimal places. When you are done, select "Compute". (In the table below, 1 is the sample size and the symbol I xy means the sum of the valuesXy.) n: 0 Sample correlation coefficient (7): I: 0 Slope (6): Ixy: 0 J-intercept (): Compute (b) Write the equation of the least-squares regression line for your data. Then on the scatter plot for your data, graph this regression equation by plotting two points and then drawing the line through them. Round each coordinate to three decimal places. Regression equation: y=0 Calf age (in months) (c) Use your regression equation to predict the weight of a 10-month-old Holstein calf on the farm. Round your answer to the nearest whole number. Predicted weight: kilograms Calf weight ( u)
Transcribed Image Text:You work for a large dairy farm and are examining the farm's techniques for rearing their Holstein calves. You want to see how large the farm's Holstein calves get as they age. So, you are going to take a random sample af 11 of the calves and note the age of each calf (denoted by X, in months) and their weight (denated by y, in ke). You will also note the product X-y of the age and the weight for each of the calves. (These products are written in the row labeled "Xy"). (a) Click an "Take Sample" to see the results for your random sample. Calf age, X 3 11 7 6 1 5 11 7 (In months) Calf welght, Tako Samplo 112 132 321 223 192 241 250 57 171 298 195 (In lg) xy 336 660 3531 1561 1152 1928 2250 855 3278 1365 Sand data to calculator v Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three dedimal places. When you are done, select "Compute". (In the table below, 1 is the sample size and the symbol I xy means the sum of the valuesXy.) n: 0 Sample correlation coefficient (7): I: 0 Slope (6): Ixy: 0 J-intercept (): Compute (b) Write the equation of the least-squares regression line for your data. Then on the scatter plot for your data, graph this regression equation by plotting two points and then drawing the line through them. Round each coordinate to three decimal places. Regression equation: y=0 Calf age (in months) (c) Use your regression equation to predict the weight of a 10-month-old Holstein calf on the farm. Round your answer to the nearest whole number. Predicted weight: kilograms Calf weight ( u)
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