Consider the following data regarding students' college GPAs and
high school GPAs. The estimated regression equation is
Estimated College GPA=3.12+0.0110(High School GPA).
College GPA | High School GPA |
---|---|
2.44 | 2.39 |
3.05 | 3.63 |
3.82 | 2.76 |
2.37 | 3.00 |
3.35 | 2.44 |
3.88 | 2.88 |
Step 1 of 3 :
Compute the sum of squared errors (SSE) for the model. Round your answer to four decimal places.
1)
X | Y | Ŷ=3.12+0.0110*x | Y - Ŷ | SSE = (Y-Ŷ)² | |||
2.39 | 2.44 | 3.147 | -0.707 | 0.50 | |||
3.63 | 3.05 | 3.160 | -0.110 | 0.012 | |||
2.76 | 3.82 | 3.151 | 0.669 | 0.448 | |||
3 | 2.37 | 3.153 | -0.783 | 0.614 | |||
2.44 | 3.35 | 3.147 | 0.203 | 0.041 | |||
2.88 | 3.88 | 3.152 | 0.728 | 0.530 | |||
total |
2.1442 |
sum of squared errors, SSE= Σ(Y-Ŷ)² = 2.1442
Consider the following data regarding students' college GPAs and high school GPAs. The estimated regression equation...
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Estimated College GPA=3.26+(−0.0361)(High School GPA). GPAs College GPA High School GPA 2.00 3.49 3.45 3.77 3.38 4.64 3.59 2.23 2.90 3.45 3.45 3.75 Step 2 of 3 : Compute the mean square error (s 2 e ) for the model. Round your answer to four decimal places.
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