Asked by Carey Sanders on Jul 20, 2024

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Given that the sum of squares for error is 60 and the sum of squares for regression is 140,then the coefficient of determination is:

A) 0.429
B) 0.300
C) 0.700
D) None of these choices.

Sum of Squares

A statistical measure that quantifies the variability or dispersion of a set of numbers by squaring their deviations from the mean.

Coefficient of Determination

A statistical measure represented by R^2, which shows the proportion of variance in the dependent variable that is predictable from the independent variables.

  • Comprehend the significance of the coefficient of determination and how it influences model fit.
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MD
Michael DeboodtJul 26, 2024
Final Answer :
C
Explanation :
The coefficient of determination (R-squared) is the ratio of the sum of squares for regression to the total sum of squares (sum of squares for regression + sum of squares for error).
Total sum of squares = sum of squares for regression + sum of squares for error = 140 + 60 = 200
Therefore, R-squared = 140/200 = 0.7.
Hence, the answer is C.