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A Second Course in Statistics: Regression Analysis, Pearson New International Edition, 7th Edition

William Mendenhall
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A Second Course in Statistics: Regression Analysis, Pearson New International Edition, 7th Edition

By William Mendenhall, Terry Sincich
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Overview
Author
William Mendenhall
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Edition
7th
ISBN
9781292042909
Published Date
20/09/2013
Pages
744

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.

Features
  • Readability was a main goal of the authors, whose intent was to create a teaching text rather than a reference text. Concepts are explained in a logical, intuitive manner with worked-out examples.
  • Model building is fundamental to any regression analysis and is introduced in Chapters 4—8, then emphasised throughout the text.
  • Development of regression skills: in addition to teaching basic concepts and methodology, this text stresses its usage in solving applied problems.
  • Real data is used in examples and exercises to maintain the applied nature of this text.
  • Examples illustrate the important aspects of model construction, data analysis, and the interpretation of results.
  • Exercises are located at the end of every section and chapter. Nearly every exercise is based on data and research extracted from news or journal articles.
  • Seven case studies address real-life research problems and are suitable for class discussion. While working through these, students can see how regression analysis is used to answer practical questions, and can then formulate appropriate statistical models for the analysis and interpretation of sample data.
  • Statistical software instruction includes the latest software packages: SAS®, SPSS®, MINITAB®
Table of contents
  • 1. A Review of Basic Concepts (Optional)
  • 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 (Optional)
  • 10. Introduction to Time Series Modeling and Forecasting
  • 11. Principles of Experimental Design
  • 12. The Analysis of Variance for Designed Experiments