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Some basic results in probability and statistics
Linear regression with one independent variable
4 J Aptness of model and remedial measures
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90 percent family 95 percent confidence alternatives analysis of variance ANOVA model appropriate calculations completely randomized design conclusion correlation decision rule degrees of freedom denoted error sum error terms experimental units F test factor A main factor effects factor level means family confidence coefficient Figure fitted regression fitted values follows Hence independent variables indicator variables interaction effects interval estimate least squares estimators level of significance linear regression model main effects matrix mean response mean squares method nonlinear regression Note observations Obtain the residuals P-value pairwise comparisons parameters percent confidence interval percent family confidence point estimate prediction prediction interval Problem reduced model Refer regression analysis regression function regression line regression model response function sample sizes single-factor SSAB SSE(F SSTO standard deviation sum of squares test statistic tion transformed treatment effects treatment means Tukey two-factor study Type I error variance model vector