Blank Filling Question. No work is required or graded. A simple linear regression analysis for n = 20 data points produced the following results: y = 2.1 + 3.4x x = 2.5 y = 10.6 SSxx = 4.77 SSyy = 59.21 SSxy = 16.22 1. Find SSE, the sum of squares of residuals. SSE= SSyy - xSSxy 2. Find s, the estimated standard error of the regression model. s2=SSE÷ and then taking square root will give s = 3. Find a 95% confidence interval for E(y) when x = 2.5. Xs.e.

MATLAB: An Introduction with Applications
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Blank Filling Question. No work is required or graded.
A simple linear regression analysis for n = 20 data points produced the following results:
%D
ŷ = 2.1 + 3.4x
x = 2.5
y = 10.6
%D
%D
SS = 4.77
SSyy = 59.21
SSxy
= 16.22
1. Find SSE, the sum of squares of residuals.
SSE= SSyy
%3D
2. Find s, the estimated standard error of the regression model.
s2=SSE÷
and then taking square root will give s =
3. Find a 95% confidence interval for E(y) when x = 2.5.
Xs.e.
Transcribed Image Text:4 Blank Filling Question. No work is required or graded. A simple linear regression analysis for n = 20 data points produced the following results: %D ŷ = 2.1 + 3.4x x = 2.5 y = 10.6 %D %D SS = 4.77 SSyy = 59.21 SSxy = 16.22 1. Find SSE, the sum of squares of residuals. SSE= SSyy %3D 2. Find s, the estimated standard error of the regression model. s2=SSE÷ and then taking square root will give s = 3. Find a 95% confidence interval for E(y) when x = 2.5. Xs.e.
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