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The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ex² = 134.17 2.9 s x s 6.2 Ey = 774.7 Ey² = 60739.23 Exy = 2832.21 %3D Before the standard error of regression, se , can be calculated, it is necessary to calculate SSyy. Enter the value for SSy accurate to the nearest tenth.

The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ex² = 134.17 2.9 s x s 6.2 Ey = 774.7 Ey² = 60739.23 Exy = 2832.21 %3D Before the standard error of regression, se , can be calculated, it is necessary to calculate SSyy. Enter the value for SSy accurate to the nearest tenth.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 4PPS
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The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ex² = 134.17 2.9 < x s 6.2 Ey = 774.7 Ey² = 60739.23 Exy = 2832.21 %3D Before the standard error of regression, se , can be calculated, it is necessary to calculate SSyy. Enter the value for SSw accurate to the nearest tenth.
Transcribed Image Text:The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ex² = 134.17 2.9 < x s 6.2 Ey = 774.7 Ey² = 60739.23 Exy = 2832.21 %3D Before the standard error of regression, se , can be calculated, it is necessary to calculate SSyy. Enter the value for SSw accurate to the nearest tenth.
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