BUSINESS ADMINISTRATION
BUSINESS ANALYTICS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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2.32
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0.43
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0.19
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0.89
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Detailed explanation-1: -SSE is the sum of squared error, SSR is the sum of squared regression, SST is the sum of squared total, n is the number of observations, and p is the number of regression coefficients. Note that p includes the intercept, so for example, p is 2 for a linear fit.
Detailed explanation-2: -where SSR is the sum of squares due to regression, SST is the total sum of squares. By “sum of squares” we mean the sum of squared deviations between actual values and the mean (SST), or between predicted values and the mean (SSR).
Detailed explanation-3: -The coefficient of determination (R²) measures how well a statistical model predicts an outcome. The outcome is represented by the model’s dependent variable. The lowest possible value of R² is 0 and the highest possible value is 1.