Questions and Answers
What is the equation for SST?
What is SST?
Total Sum of Squares
What does SSR stand for?
Sum of Squares due to Regression
What does SSE stand for?
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How is SST calculated?
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How is SSR calculated?
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How is SSE calculated?
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What is r^2 in regression analysis?
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Study Notes
Sum of Squares Overview
- SST (Total Sum of Squares) represents the total variability in the dependent variable.
- The formula relating the concepts is: SST = SSR + SSE.
Definitions of Key Components
- SSR (Sum of Squares Due to Regression) quantifies the variation explained by the regression model.
- SSE (Sum of Squares Due to Error) measures the variation not explained by the model, indicating the residual error.
Calculations
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To calculate SST:
- Use the formula Sum(yi - averagey)², where yi represents each observed value and averagey is the mean of those values.
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To calculate SSR:
- Use the formula Sum(yhat - averagey)², where yhat is the predicted value from the regression model.
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To calculate SSE:
- Use the formula Sum(yi - yhat)², measuring the discrepancies between observed values and predicted values.
Coefficient of Determination
- The R² value is defined as SSR/SST, representing the proportion of the variance in the dependent variable that is predictable from the independent variable(s).
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Description
This quiz covers key concepts related to the total sum of squares (SST), sum of squares due to regression (SSR), and sum of squares due to error (SSE). Each flashcard provides essential definitions and mathematical calculations needed for understanding these statistical terms. Test your knowledge of these fundamental statistical concepts.
