Statistics for Business & Economics, Global Edition

Author:   James T. McClave ,  P. Benson ,  Terry Sincich ,  Terry Sincich
Publisher:   Pearson Education Limited
Edition:   14th edition
ISBN:  

9781292413396


Pages:   896
Publication Date:   24 November 2021
Format:   Paperback
Availability:   Available To Order   Availability explained
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Statistics for Business & Economics, Global Edition


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Overview

Statistics for Business and Economics introduces statistics in the context of contemporary business. Emphasising statistical literacy in thinking, the text applies its concepts with real data and uses technology to develop a deeper conceptual understanding. Examples, activities, and case studies foster active learning in the classroom while emphasising intuitive concepts of probability and teaching students to make informed business decisions. The 14th Edition continues to highlight the importance of ethical behaviour in collecting, interpreting, and reporting on data, while also providing a wealth of new and updated exercises and case studies.

Full Product Details

Author:   James T. McClave ,  P. Benson ,  Terry Sincich ,  Terry Sincich
Publisher:   Pearson Education Limited
Imprint:   Pearson Education Limited
Edition:   14th edition
Dimensions:   Width: 21.60cm , Height: 3.40cm , Length: 27.60cm
Weight:   1.840kg
ISBN:  

9781292413396


ISBN 10:   1292413395
Pages:   896
Publication Date:   24 November 2021
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Statistics, Data, and Statistical Thinking 2. Methods for Describing Sets of Data 3. Probability 4. Random Variables and Probability Distributions 5. Sampling Distributions 6. Inferences Based on a Single Sample: Estimation with ConfidenceIntervals 7. Inferences Based on a Single Sample: Tests of Hypotheses 8. Inferences Based on Two Samples: Confidence Intervals and Testsof Hypotheses 9. Design of Experiments and Analysis of Variance 10. Categorical Data Analysis 11. Simple Linear Regression 12. Multiple Regression and Model Building 13. Methods for Quality Improvement: Statistical Process Control(Available Online) 14. Time Series: Descriptive Analyses, Models, and Forecasting(Available Online) 15. Nonparametric Statistics (Available Online)   Appendix A: Summation Notation Appendix B: Basic Counting Rules Appendix C: Calculation Formulas for Analysis of Variance C.1 Formulas for the Calculationsin the Completely Randomized Design C.2 Formulas for the Calculationsin the Randomized Block Design C.3 Formulas for the Calculationsfor a Two-Factor Factorial Experiment C.4 Tukey's Multiple ComparisonsProcedure (Equal Sample Sizes) C.5 Bonferroni MultipleComparisons Procedure (Pairwise Comparisons) C.6 Scheffé's MultipleComparisons Procedure (Pairwise Comparisons) Appendix D: Tables   Answers to Selected Exercises Index Credits   

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Author Information

Dr. Jim McClave is currently President and CEO ofInfo Tech, Inc., a statistical consulting and software development firm with aninternational clientele. He is also a Courtesy Professor ofStatistics at the University of Florida, where he was a full-time member of thefaculty for over 20 years. Dr. Terry Sincich obtained his PhD inStatistics from the University of Florida in 1980. He is a ProfessorEmeritus of the Information Systems & Decision SciencesDepartment at the University of South Florida in Tampa, where hewas responsible for teaching basic statistics to all undergraduates, aswell as advanced statistics to all doctoral candidates, in the College ofBusiness Administration. He has published articles in such journals asthe Journal of the American Statistical Association, InternationalJournal of Forecasting, Academy of Management Journal,and Auditing: A Journal of Practice & Theory.Dr. Sincich is a co-author of the texts: Statistics, Statisticsfor Business & Economics, Statistics for Engineering & theSciences, and A Second Course in Statistics: Regression Analysis.

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