STATS 2B03 Chapter Notes - Chapter 10: Null Hypothesis, Test Statistic, Dependent And Independent Variables
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This assumptions distinguishes the multiple regression model from the multiple correlation model. This condition indicates that any inferences that are drawn from sample data apply only to the set of x values observed and not to some larger collection of x"s. Under the regression model, correlation analysis is not meaningful. For each set of xi values there is a subpopulation of y values. To construct certain confidence intervals and test hypotheses, it must be known, or the researcher must be willing to assume, that these subpopulations of y values are normally distributed. Since we will want to demonstrate these inferential procedures, the assumption of normality will be made. The variances of the subpopulation of y are all equal. That is, the values of y selected for one set of x values do not depend on the values of y selected at another set of x values. 10. 3 obtaining the multiple regression equation sum of squares of deviations: .