A Second Course in Business Statistics: Regression Analysis |
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analysis of variance ANOVA appraised assumptions autocorrelation autoregressive B₁ B₁x1 B₂ Calculate coefficient coefficient of determination completely randomized design confidence interval correlation degrees of freedom DEP MEAN C.V. difference distribution dollars evidence to indicate example experimental exponentially smoothed F VALUE F-statistic F-test factorial experiment factors first-order model fit the model forecast graph increase INTERCEP main effects measurements method Minitab model E(y model for E(y moving average multicollinearity multiple regression null hypothesis observations obtained package PARAMETER=0 predicted value prediction interval PROB procedure qualitative independent variables quantitative R-SQUARE random error ratio regression analysis regression model Rejection region response ROOT MSE sales engineer sample means SAS printout second-order model Section series model shown in Figure squares model ẞ parameters SS(Total SSE2 ẞo standard deviation STANDARD ERROR straight-line model SUM OF SQUARES test statistic treatment means trend VALUE PROB>F x₁