Regression Word Scramble
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Term | Definition |
Classical Assumption #1 | The regression model is linear, is correctly specified, and has an additive error term. |
Classical Assumption #2 | The error term has a zero population mean. |
Classical Assumption #3 | All explanatory variables are uncorrelated with the error term. |
Classical Assumption #4 | Observations of the error term are uncorrelated with each other. (no serial correlation) |
Classical Assumption #5 | The error term has a constant variance. (no heteroskedasticity) |
Classical Assumption #6 | No explanatory variable is a perfect linear function of any other explanatory variable(s). (no perfect multicollinearity) |
Classical Assumption #7 | The error term is normally distributed. (this assumption is optional but usually is invoked) |
Created by:
kristel387
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