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Simple linear regression
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ACPT algorithm analysis of variance assumptions Berkeley Guidance Study Chapter coefficient collinearity column computed confidence interval consider covariance data set defined degrees of freedom deleted depend DLIC dummy variables effect ellipsoid equation example F-test Figure fitted model fitted values Forbes full model function given in Table graph I I I I independent variables lack of fit least squares estimates linear model linear regression matrix mean square measured methods multiple regression normally distributed observed data observed values obtained Old Faithful geyser outlier prediction interval predictors principal components procedure quantities random variables rankit relationship Residual plot residual sum ro ro ro sample correlation scale scatter plot silver iodide simple regression model SSreg statistics straight line Studentized residuals subset model sum of squares summary Suppose tion transformation usual var(e versus weighted least squares zero