An introduction to statistical methods & data analysis / R. Lyman Ott and Michael Longnecker.

Includes index.

Chapter1. Statistics and the Scientific Method -- Chapter2. Using Surveys and Experimental Studies to Gather Data -- Chapter3. Data Description -- Chapter4. Probability and Probability Distributions -- Chapter5. Inferences about Population Central Values -- Chapter6. Inferences Comparing Two Population Central Values -- Chapter7. Inferences about Population Variances Chapter8. Inferences About More Than Two Population Central Values -- Chapter9. Multiple Comparisons -- Chapter10. Categorical Data -- Chapter11. Linear Regression and Correlation -- Chapter12. Multiple Regression and the General Linear Model -- Chapter13. Further Regression Topics -- Chapter14. Analysis of Variance for Completely Randomized Designs -- Chapter15. Analysis of Variance for Blocked Designs -- Chapter16. Analysis of Covariance -- Chapter17. Analysis of Variance for Some Fixed-, Random-, and Mixed-Effects Models -- Chapter18. Split-Plot, Repeated Measures, and Crossover Designs -- Chapter19. Analysis of Variance for Some Unbalanced Designs .

Seventh Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments