Applied statistics: analysis of variance and regression
Descriptive statistics. Statistical inference: populations and samples. Inference from a single sample. Samples from two populations. One-way analysis of variance: fixed effects model. Hierarchical or nested design. Two-way analysis of variance: fixed effects model. Three-way analysis of variance: fixed effects model. Factorial designs with each factor at two levels. Variable effects models. Repeated measure designs. Linear regression and correlation. Multiple regression: the fixed X model. Multiple regression and correlation analysis. Analysis of covariance. Data screening.
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Populations and Samples
Inference from a Single Sample
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analysis of variance assumptions blood pressure BMDP calculated Chapter classification compared confidence interval correlation coefficient curve degrees of freedom denoted diet differences discussed due regression EMS column equal example expected value experiment F statistic F test factor fixed effects model formula given groups histogram individuals interaction investigator level confidence interval linear combinations mean square method multiple regression nested normal distribution null hypothesis number of observations obtained one-way analysis outliers overall mean parameters plane plots point estimates polynomial population mean population regression lines population variance problem procedure quadratic random sample rats regression analysis regression coefficients regression equation residual sum sample means scatter diagram standard deviation statistically independent straight line subset sum of squares test H0 test of H0 three-way tion transformation treatment combination two-way variable effects model variance component variance table weight Wiley wish yield Yijk zero