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Berenson’s clear and consistent explanations of how and why accepted statistical techniques are used and fresh, conversational writing style helps students with their comprehension of the concepts.
Berenson’s ‘real world’ business focus takes students beyond the pure theory by connecting statistical concepts to functional areas of business through engaging examples. Examples of real people working in real business environments, using statistics to tackle real business challenges bring the subject to life.
Dr Nicola Jayne is a lecturer in the Southern Cross Business School at the Lismore campus of Southern Cross University. She has been teaching quantitative units since being appointed to the university in 1993 after several years at Massey University in New Zealand. Nicola has lectured extensively in Business and Financial Mathematics, Discrete Mathematics and Statistics, both undergraduate and postgraduate, as well as various Pure Mathematics units. Her academic qualifications from Massey University include a Bachelor of Science (majors in Mathematics and Statistics), a Bachelor of Science with Honours (first class) and a Doctor of Philosophy, both in Mathematics. Nicola also has a Graduate Certificate in Higher Education (Learning & Teaching) from Southern Cross University. She was the recipient of a Vice Chancellor’s Citation for an Outstanding Contribution to Student Learning in 2011.
Dr Martin O’Brien is a senior lecturer and Head of the Discipline of Economics at the School of Economics, University of Wollongong. Martin earned his Bachelor of Commerce (first-class honours) and PhD in Economics at the University of Newcastle. Martin’s PhD and subsequent published research is in the general area of labour economics, and specifically the exploration of older workers’ labour force participation in Australia in the context of an ageing society. He has taught a wide range of quantitative subjects at university level, including business statistics, quantitative analysis for decision making, econometrics, financial modelling, business research methods and quality management. Martin also has a keen interest in the development of new teaching technologies and the analysis of alternative teaching methods such as practice-into-theory.
About the originating authors
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 currently 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 and an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. Berenson’s 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. In 2005, he was the first recipient of the Catherine A. Becker Service for Educational Excellence Award at Montclair State University, and in 2012 he was the recipient of the Khubani/Telebrands Faculty Research Fellowship in the School of Business.
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 recognised in the United States 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. Levine is also the co-author of Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, currently in its second edition, Six Sigma for Green Belts and Champions, and Design for Six Sigma for Green Belts and Champions; and is the author of Statistics for Six Sigma Green Belts, all published by FT Press, a Pearson imprint; and Quality Management, third edition, published by McGraw-Hill/Irwin. He is also the author of Video Review of Statistics and Video Review of Probability, both published by Video Aided Instruction, and the statistics module of the MBA primer published by Cengage Learning. 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.
Kathryn A. Szabat is Associate Professor and Chair of Business Systems and Analytics at LaSalle University. She teaches undergraduate and graduate courses in business statistics and operations management. Szabat’s research has been published in International Journal of Applied Decision Sciences, Accounting Education, Journal of Applied Business and Economics, Journal of Healthcare Management, and Journal of Management Studies. Scholarly chapters have appeared in Managing Adaptability, Intervention, and People in Enterprise Information Systems; Managing, Trade, Economies and International Business; Encyclopedia of Statistics in Behavioral Science; and Statistical Methods in Longitudinal Research. Szabat has provided statistical advice to numerous business, non-business and academic communities. Her more recent involvement has been in the areas of education, medicine and non-profit capacity building. Szabat received a BS in mathematics from State University of New York at Albany and MS and PhD degrees in statistics, with a cognate in operations research, from the Wharton School of the University of Pennsylvania.
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