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TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, Jeffrey D. Camm, and James J. Cochran provide an accurate timely presentation of statistical concepts you and your students can trust with every edition.

LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique problem-scenario approach guides students in understanding statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how professionals regularly use statistics in business to solve problems.

SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn to use techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and the use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems.

USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today's students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today's most popular statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.

COVERAGE HIGHLIGHTS DATA MINING, BIG DATA AND ANALYTICS. A proven section on analytics describes what analytics is, the types of analytics used in business and how this relates to statistics. An expanded section on data mining includes a discussion of big data and how businesses today are using data mining to establish competitive advantages.

Preface.

1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Displays.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Tests.
10. Inference about Means and Proportions with Two Populations.
11. Inferences about Population Variances.
12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.
13. Experimental Design and Analysis of Variance.
14. Simple Linear Regression.
15. Multiple Regression.
16. Regression Analysis: Model Building.
17. Time Series Analysis and Forecasting.
18. Nonparametric Methods.
19. Statistical Methods for Quality Control.
20. Index Numbers.
21. Decision Analysis (On Website).
22. Sample Survey (On Website).

Appendix A: References and Bibliography.
Appendix B: Tables.
Appendix C: Summation Notation.
Appendix D: Self-Test Solutions and Answers to Even –Numbered Exercises.
Appendix E: Microsoft Excel 2016 and Tools for Statistical Analysis.
Appendix F: Computing p-Values Using Minitab and Excel.
Index.