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Locate the values of SSE, s2, and s on the printout below.

Model Summary


Model
R
R Square Adjusted
R Square Std. Error of the Estimate
1 .859 .737 .689 11.826
ANOVA

Model Sum of Squares df Mean Square F Sig.
1 Regression 4512.024 1 4512.024 32.265 .001
Residual 1678.115 12 139.843
Total 6190.139 13
Question 3 options:

SSE = 4512.024; s2 = 4512.024; s = 32.265

SSE = 4512.024; s2 = 139.843; s = 11.826

SSE = 6190.139; s2 = 4512.024; s = 32.265

SSE = 1678.115; s2 = 139.843; s = 11.826

Respuesta :

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Answer:

SSE = 1678.115; s2 = 139.843; s = 11.826

Explanation:

Consider the following formulas:

SSE: This value provides a measure of how well the line of best fit approximates the data set.

S^2: The variance is mathematically defined as the average of the squared differences from the mean

S: is the expectation of the squared deviation of a random variable from its mean.

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