Regression Terminology: Deterministic modes-Regression formulas that predict an exact value. Probabilistic modes-Regression formulas that take into account random error, and the fact that other variables account for some of the variation in the values of y. What we use in statistics. Residual-Error of the regression line at a particular point. Difference between y (real y) and ŷ (predicted y). Heteroscedasticity-Error variance that is no constant. Homoscedasticity-Constant error variance. Standard error of the estimate (s e )-A measure of how much error is in the regression model. Need to have a lot of contend knowledge of what is being estimated to fully use the s e . Sum of Squares Error (SSE = ∑(y - ŷ) 2 )-Some of the types of Regression Analysis- we are trying to predict y and x . Simple Regression Analysis : predicting a continuous y variable from a continuous x variable. Logistic Regression Analysis : predicting a dichotomous y variable from one or more continuous x variables.
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