Homework Soursea Using the pairs of values for all 10 points find the equat
a. Using the pairs of values for all 10 points, find the equation of the regression line.
b. After removing the point with coordinates (2,8)?, use the pairs of values for the remaining 9 points and find the equation of the regression line.
c. Compare the results from parts? (a) and? (b).
| a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,8)?, use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts? (a) and? (b).
|
![\"3](\"//d2vlcm61l7u1fs.cloudfront.net/media%2F4c7%2F4c7632ed-c8f9-4c2c-9804-a5833f079cbf%2FphpyWSkdl.png\")
Solution
MINITAB used for analysis.
a).
Regression Analysis: y versus x
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 10.165 10.165 7.94 0.023
x 1 10.165 10.165 7.94 0.023
Error 8 10.235 1.279
Lack-of-Fit 2 4.235 2.118 2.12 0.201
Pure Error 6 6.000 1.000
Total 9 20.400
Model Summary
S R-sq R-sq(adj) R-sq(pred)
1.13111 49.83% 43.56% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 8.35 1.45 5.77 0.000
x -0.706 0.250 -2.82 0.023 1.00
Regression Equation
y = 8.35 - 0.706 x
Fits and Diagnostics for Unusual Observations
Std
Obs y Fit Resid Resid
10 8.000 6.941 1.059 1.82 X
X Unusual X
b).
Regression Analysis: y versus x
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 0.00000 0.00000 0.00 1.000
x 1 0.00000 0.00000 0.00 1.000
Error 7 6.00000 0.85714
Lack-of-Fit 1 0.00000 0.00000 0.00 1.000
Pure Error 6 6.00000 1.00000
Total 8 6.00000
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.925820 0.00% 0.00% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 4.00 2.29 1.75 0.124
x 0.000 0.378 0.00 1.000 1.00
Regression Equation
y = 4.00 + 0.000 x
c).
After removing the point with coordinates (2,8), there is no relation between x and y. The variable x is not useful for predicting y.
