Flexible organization

makes the text appropriate for use in a one or two term course.

Praised for the quality and accuracy of the exercise sets, the authors use a spiraling technique which reintroduces exercises and examples seen previously so that students may apply their growing knowledge of statistics to a familiar problem and data set.

Complete case studies are presented in material dealing with two-sample inference, one-and two-factor analysis of variance, multifactor analysis of variance, and the analysis of 2^k factorial experiments.

NEW--Greater than 20% of the exercises and examples have been updated with new real data.

The standard, boring cards and "balls and urns" examples in the probability chapters have largely been replaced with exercises addressing the scientific aspects of everyday life.

Many new exercises and applications of the poisson, binomial, geometric, hypergeometric, and gamma distributions have been introduced.

NEW--The coverage of maximum likelihood has been expanded to include many new exercises and examples. New material using linear models with matrix development has been added to the coverage of "Analysis of Variance in Regression."

NEW--The book has been redesigned to insure that each figure is presented in closer proximity to the example it illustrates to eliminate the need to flip back and forth between pages in the book. The Answer Appendix now includes answers to the odd exercises only.

NEW--Recognizing the importance of the computer in data analysis, many new SAS and Minitab printouts have been added to the book in numerous chapters including those dealing with two samples (Chs. 9, 10), simple linear regression (Ch. 11), multiple regression (Ch. 12), one factor experiments (Ch. 13), two level factorial (Ch. 14)and fractional factorial experiments (Ch 15).

NEW--In addition some exercises are presented as Case Studies in which a computer printout is presented from which the student is asked to draw conclusions. These exercises refine the students ability to draw conclusions from data and interpret summary results in the most meaningful way.

...show morePraised for the quality and accuracy of the exercise sets, the authors use a spiraling technique which reintroduces exercises and examples seen previously so that students may apply their growing knowledge of statistics to a familiar problem and data set.

Complete case studies are presented in material dealing with two-sample inference, one-and two-factor analysis of variance, multifactor analysis of variance, and the analysis of 2^k factorial experiments.

NEW--Greater than 20% of the exercises and examples have been updated with new real data.

The standard, boring cards and "balls and urns" examples in the probability chapters have largely been replaced with exercises addressing the scientific aspects of everyday life.

Many new exercises and applications of the poisson, binomial, geometric, hypergeometric, and gamma distributions have been introduced.

NEW--The coverage of maximum likelihood has been expanded to include many new exercises and examples. New material using linear models with matrix development has been added to the coverage of "Analysis of Variance in Regression."

NEW--The book has been redesigned to insure that each figure is presented in closer proximity to the example it illustrates to eliminate the need to flip back and forth between pages in the book. The Answer Appendix now includes answers to the odd exercises only.

NEW--Recognizing the importance of the computer in data analysis, many new SAS and Minitab printouts have been added to the book in numerous chapters including those dealing with two samples (Chs. 9, 10), simple linear regression (Ch. 11), multiple regression (Ch. 12), one factor experiments (Ch. 13), two level factorial (Ch. 14)and fractional factorial experiments (Ch 15).

NEW--In addition some exercises are presented as Case Studies in which a computer printout is presented from which the student is asked to draw conclusions. These exercises refine the students ability to draw conclusions from data and interpret summary results in the most meaningful way.

Flexible organization makes the text appropriate for use in a one or two term course.

Praised for the quality and accuracy of the exercise sets, the authors use a spiraling technique which reintroduces exercises and examples seen previously so that students may apply their growing knowledge of statistics to a familiar problem and data set.

Complete case studies are presented in material dealing with two-sample inference, one-and two-factor analysis of variance, multifactor analysis of variance, and the analysis of 2^k factorial experiments.

NEW--Greater than 20% of the exercises and examples have been updated with new real data.

The standard, boring cards and "balls and urns" examples in the probability chapters have largely been replaced with exercises addressing the scientific aspects of everyday life.

Many new exercises and applications of the poisson, binomial, geometric, hypergeometric, and gamma distributions have been introduced.

NEW--The coverage of maximum likelihood has been expanded to include many new exercises and examples. New material using linear models with matrix development has been added to the coverage of "Analysis of Variance in Regression."

NEW--The book has been redesigned to insure that each figure is presented in closer proximity to the example it illustrates to eliminate the need to flip back and forth between pages in the book. The Answer Appendix now includes answers to the odd exercises only.

NEW--Recognizing the importance of the computer in data analysis, many new SAS and Minitab printouts have been added to the book in numerous chapters including those dealing with two samples (Chs. 9, 10), simple linear regression (Ch. 11), multiple regression (Ch. 12), one factor experiments (Ch. 13), two level factorial (Ch. 14)and fractional factorial experiments (Ch 15).

NEW--In addition some exercises are presented as Case Studies in which a computer printout is presented from which the student is asked to draw conclusions. These exercises refine the students ability to draw conclusions from data and interpret summary results in the most meaningful way. ...show less

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