Asked by Carey Sanders on Jul 20, 2024
Verified
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.
Verified Answer
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.
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.
Learning Objectives
- Comprehend the significance of the coefficient of determination and how it influences model fit.
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