Australasian and Pacific data included Request a digital sample - for educators >
Extending the teaching foundation of the previous editions, Basic Business Statistics uses a real-world focus. This allows students to visualise how the content can be applied to people and businesses in reality, helping take them look beyond concepts to visualise the theory in a tangible framework.
Using language that is more accessible - but no less authoritative - students can spend more time learning the theories with local examples and a variety of features.
Academics are given the flexibility of designing an engaging unit for a mixed cohort of students with courseware that drives technical and soft skills through authentic learning tools and assignments for hybrid, online and face-to-face units.
PHStat is an add-in for Microsoft Excel offered by Pearson that simplifies the task of operating Excel. PHStat creates real Excel worksheets that use in-worksheet calculations. PHStat comes packaged as a zip file archive that you download and unzip to the folder of your choice.
Samples Download the detailed table of contents >
Preview sample pages from Basic Business Statistics >
Student resources: These extra resources include bonus chapters, cases and data sets - Australasian and Pacific data sets are used for the problems in each chapter.
Continuing cases >
Chapters 16-21 >
Excel data sets >
Table of Contents:
- PART 1 Presenting and Describing Information
- 1 Defining and Collecting Data
- 2 Organising and Visualising Data
- 3 Numerical Descriptive Measures
- PART 2 Measuring Uncertainty
- 4 Basic Probability
- 5 Some Important Discrete Probability Distributions
- 6 The Normal Distribution and Other Continuous Distributions
- 7 Sampling Distributions
- PART 3 Drawing Conclusions about Populations Based only on Sample Information
- 8 Confidence Interval Estimation
- 9 Fundamentals of Hypothesis Testing: One-Sample Tests
- 10 Hypothesis Testing: Two-Sample Tests
- 11 analysis of Variance
- PART 4 Determining Cause and Making Reliable Forecasts
- 12 Simple Linear Regression
- 13 Introduction To Multiple Regression
- 14 Time-Series Forecasting and Index Numbers
- 15 Chi-Square Tests
- PART 5 Further Topics in Stats [ONLINE CHAPTERS]
- 16 Multiple Regression Model Building
- 17 Decision Making
- 18 Statistical Applications In Quality Management
- 19 Further Non-Parametric Tests
- 20 Business Analytics
- 21 Data Analysis: The Big Picture
- Appendices A To F
- Glossary
- Index
Download the detailed table of contents >.
About the Author :
Mark L. Berenson is Professor of Management and Information Systems at Montclair State University (Montclair, New Jersey) and also Professor Emeritus of Statistics and Computer Information Systems at Bernard M. Baruch College (City University of New York). He teaches graduate and undergraduate courses in statistics and in operations management in the School of Business and an undergraduate course in international justice and human rights that he co-developed in the College of Humanities and Social Sciences. Berenson received a BA in economic statistics, an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. His research has been published in Decision Sciences Journal of Innovative Education, Review of Business Research, The American Statistician, Communications in Statistics, Psychometrika, Educational and Psychological Measurement, Journal of Management Sciences and Applied Cybernetics, Research Quarterly, Stats Magazine, The New York Statistician, Journal of Health Administration Education, Journal of Behavioral Medicine and Journal of Surgical Oncology. His invited articles have appeared in The Encyclopedia of Measurement & Statistics and Encyclopedia of Statistical Sciences. He is co-author of 11 statistics texts published by Prentice Hall, including Statistics for Managers Using Microsoft Excel, Basic Business Statistics: Concepts and Applications and Business Statistics: A First Course. Over the years, Berenson has received several awards for teaching and for innovative contributions to statistics education.
David M. Levine is Professor Emeritus of Statistics and Computer Information Systems at Baruch College (City University of New York). He received BBA and MBA degrees in statistics from City College of New York and a PhD from New York University in industrial engineering and operations research. He is nationally recognised as a leading innovator in statistics education and is the co-author of 14 books, including such best-selling statistics textbooks as Statistics for Managers Using Microsoft Excel, Basic Business Statistics: Concepts and Applications, Business Statistics: A First Course and Applied Statistics for Engineers and Scientists Using Microsoft Excel and Minitab. He also is the co-author of Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, Six Sigma for Green Belts and Champions and Design for Six Sigma for Green Belts and Champions, and the author of Statistics for Six Sigma Green Belts and Quality Management. He has published articles in various journals, including Psychometrika, The American Statistician, Communications in Statistics, Decision Sciences Journal of Innovative Education, Multivariate Behavioral Research, Journal of Systems Management, Quality Progress and The American Anthropologist, and he has given numerous talks at the Decision Sciences Institute (DSI), American Statistical Association (ASA) and Making Statistics More Effective in Schools and Business (MSMESB) conferences. Levine has also received several awards for outstanding teaching and curriculum development from Baruch College.
As Associate Professor of Business Systems and Analytics at La Salle University, Kathryn Szabat has transformed several business school majors into one interdisciplinary major that better supports careers in new and emerging disciplines of data analysis including analytics. Szabat strives to inspire, stimulate, challenge, and motivate students through innovation and curricular enhancements and shares her coauthors' commitment to teaching excellence and the continual improvement of statistics presentations. Beyond the classroom she has provided statistical advice to numerous business, nonbusiness, and academic communities, with particular interest in the areas of education, medicine, and non-profit capacity building. Her research activities have led to journal publications, chapters in scholarly books, and conference presentations. Szabat is a member of the American Statistical Association (ASA), DSI, Institute for Operation Research and Management Sciences (INFORMS), and DSI DASI. She received a B.S. from SUNY-Albany, an M.S. in statistics from the Wharton School of the University of Pennsylvania, and a Ph.D. in statistics, with a cognate in operations research, from the Wharton School of the University of Pennsylvania.
