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The Second Course in Statistics is an increasingly important offering since more students are arriving at college having taken AP Statistics in high school. Mendenhall/Sincich’s A Second Course in Statistics is the perfect book for courses that build on the knowledge students gain in AP Statistics, or the freshman Introductory Statistics course.  A Second Course in Statistics: Regression Analysis, 7th Edition, focuses on building linear statistical models and developing skills for implementing regression analysis in real situations. This text offers applications for engineering, sociology, psychology, science, and business. The authors use real data and scenarios extracted from news articles, journals, and actual consulting problems to show how to apply the concepts. In addition, seven case studies, now located throughout the text after applicable chapters, invite students to focus on specific problems, and are suitable for class discussion. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

A Second Course in Statistics: Pearson New International Edition

• Table of Contents


• 1. A Review of Basic Concepts


• 2. Introduction to Regression Analysis


• 3. Simple Linear Regression


• 4. Multiple Regression Models


• 5. Principles of Model Building


• 6. Variable Screening Methods


• 7. Some Regression Pitfalls


• 8. Residual Analysis


• 9. Special Topics in Regression


• 10. Introduction to Time Series Modeling and Forecasting


• 11. Principles of Experimental Design


• 12. The Analysis of Variance for Designed Experiments


• Appendix: Derivation of the Least Squares Estimates of ss0 and ss1 in Simple Linear Regression


• Appendix: The Mechanics of a Multiple Regression Analysis


• Appendix: A Procedure for Inverting a Matrix


• Appendix: Useful Statistical Tables


• Normal Curve Areas Table


• Critical Values for Student's t


• Index


• A


• B


• C


• D


• E


• F


• G


• H


• I


• L


• M


• N


• O


• P


• Q


• R


• S


• T


• U


• V


• W


• X


• Y


• Z