Statistics for Research / Edition 3 available in Hardcover
Praise for the Second Edition
"Statistics for Research has other fine qualities besidessuperior organization. The examples and the statistical methods arelaid out with unusual clarity by the simple device of using specialformats for each. The book was written with great care and isextremely user-friendly."—The UMAP Journal
Although the goals and procedures of statistical research havechanged little since the Second Edition of Statistics for Researchwas published, the almost universal availability of personalcomputers and statistical computing application packages have madeit possible for today's statisticians to do more in less time thanever before.
The Third Edition of this bestselling text reflects how thechanges in the computing environment have transformed the waystatistical analyses are performed today. Based on extensive inputfrom university statistics departments throughout the country, theauthors have made several important and timely revisions,including:
- Additional material on probability appears early in thetext
- New sections on odds ratios, ratio and difference estimations,repeated measure analysis, and logistic regression
- New examples and exercises, many from the field of the healthsciences
- Printouts of computer analyses on all complex procedures
- An accompanying Web site illustrating how to use SAS® andJMP® for all procedures
The text features the most commonly used statistical techniquesfor the analysis of research data. As in the earlier editions,emphasis is placed on how to select the proper statisticalprocedure and how to interpret results. Whenever possible, to avoidusing the computer as a "black box" that performs a mysteriousprocess on the data, actual computational procedures are alsogiven.
A must for scientists who analyze data, professionals andresearchers who need a self-teaching text, and graduate students instatistical methods, Statistics for Research, Third Edition bringsthe methodology up to date in a very practical and accessibleway.
About the Author
SHIRLEY DOWDY, PhD, has held appointments as Professor ofStatistics at West Virginia University and Professor of ResearchMethodology at St. Louis University, where she was also the Dean ofthe College of Arts and Sciences and from which she is now retired.She received her PhD from the University of Notre Dame.
STANLEY WEARDEN, PhD, is currently a professor in theDepartment of Statistics at West Virginia University in Morgantown,West Virginia, where he previously served for four years asChairman of the Department of Statistics and Computer Science. Heearned his PhD in population genetics from Cornell University andalso held the position of Fulbright Professor of Statistics at theUniversity of the West Indies.
DANIEL CHILKO, MS, is an Associate Professor ofStatistics at West Virginia University and has contributed hisexpertise to several books in the field. He received his MS fromRutgers University.
Table of Contents
Preface to the Third Edition.
Preface to the Second Edition.
Preface to the First Edition.
1. The Role of Statistics.
1.1 The Basic Statistical Procedure.
1.2 The Scientific Method.
1.3 Experimental Data and Survey Data.
1.4 Computer Usage.
2. Populations, Samples, and ProbabilityDistributions.
2.1 Populations and Samples.
2.2 Random Sampling.
2.3 Levels of Measurement.
2.4 Random Variables and Probability Distributions.
2.5 Expected Value and Variance of a ProbabilityDistribution.
3. Binomial Distributions.
3.1 The Nature of Binomial Distributions.
3.2 Testing Hypotheses.
3.4 Nonparametric Statistics: Median Test.
4. Poisson Distributions.
4.1 The Nature of Poisson Distributions.
4.2 Testing Hypotheses.
4.4 Poisson Distributions and Binomial Distributions.
5. Chi-Square Distributions.
5.1 The Nature of Chi-Square Distributions.
5.2 Goodness-of-Fit Tests.
5.3 Contingency Table Analysis.
5.4 Relative Risks and Odds Ratios.
5.5 Nonparametric Statistics: Median Test for SeveralSamples.
6. Sampling Distribution of Averages.
6.1 Population Mean and Sample Average.
6.2 Population Variance and Sample Variance.
6.3 The Mean and Variance of the Sampling Distribution ofAverages.
6.4 Sampling Without Replacement.
7. Normal Distributions.
7.1 The Standard Normal Distribution.
7.2 Inference From a Single Observation.
7.3 The Central Limit Theorem.
7.4 Inferences About a Population Mean and Variance.
7.5 Using a Normal Distribution to Approximate OtherDistributions.
7.6 Nonparametric Statistics: A Test Based on Ranks.
8. Student’s tDistribution.
8.1 The Nature of t Distributions.
8.2 Inference About a Single Mean.
8.3 Inference About Two Means.
8.4 Inference About Two Variances.
8.5 Nonparametric Statistics: Matched-Pair and Two-Sample RankTests.
9. Distributions of Two Variables.
9.1 Simple Linear Regression.
9.2 Model Testing.
9.3 Inferences Related to Regression.
9.5 Nonparametric Statistics: Rank Correlation.
9.6 Computer Usage.
9.7 Estimating Only One Linear Trend Parameter.
10. Techniques for One-way Analysis of Variance.
10.1 The Additive Model.
10.2 One-Way Analysis-of-Variance Procedure.
10.3 Multiple-Comparison Procedures.
10.4 One-Degree-of-Freedom Comparisons.
10.6 Bonferroni Procedures.
10.7 Nonparametric Statistics: Kruskal–Wallis ANOVA forRanks.
11. The Analysis-of-Variance Model.
11.1 Random Effects and Fixed Effects.
11.2 Testing the Assumptions for ANOVA.
12. Other Analysis-of-Variance Designs.
12.1 Nested Design.
12.2 Randomized Complete Block Design.
12.3 Latin Square Design.
12.4 a xb Factorial Design.
12.5 a xb xc Factorial Design.
12.6 Split-Plot Design.
12.7 Split Plot with Repeated Measures.
13. Analysis of Covariance.
13.1 Combining Regression with ANOVA.
13.2 One-Way Analysis of Covariance.
13.3 Testing the Assumptions for Analysis of Covariance.
13.4 Multiple-Comparison Procedures.
14. Multiple Regression and Correlation.
14.1 Matrix Procedures.
14.2 ANOVA Procedures for Multiple Regression andCorrelation.
14.3 Inferences About Effects of Independent Variables.
14.4 Computer Usage.
14.5 Model Fitting.
14.6 Logarithmic Transformations.
14.7 Polynomial Regression.
14.8 Logistic Regression.
Appendix of Useful Tables.
Answers to Most Odd-Numbered Exercises and All ReviewExercises.
What People are Saying About This
"The text is easy to read, and students will enjoy the wide range of examples and illustrations…a nice improvement over the first and second editions." (Technometrics, February 2005)