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About this book
This textbook provides a thorough treatment of major statistical methods and techniques for both staticticians and non-statisticians requiring a foundation in applied statistics. There is an emphasis throughout on inference from data, the principle of fitting models by least squares, and careful interpretation of results. The authors employ SAS to produce PC-based statistical graphics and perform some analyses where appropriate. This edition includes updated real-world data sets.
Observations; probability; sampling from a normal distribution; comparisons involving two sample means; principles of experimental design; analysis of variance I - the one-way classification; mutiple comparisons; analysis of variance II - multiway classification; linear regression; linear correlation; matrix notation; linear regression in matrix notation; multiple and partial regression and correlation; analysis of variance III - factorial experiments; analysis of variance; analysis of covariance IV; analysis of covariance; analysis of variance V - unequal subclass numbers; some uses of chi-square; enumeration data I - one-way classifications; enumeration data II - contingency tables; categorical models; some discrete distributions; nonparametric statistics; sampling finite populations.