Practical Business Statistics

by Andrew F. Siegel

Overview

Practical Business Statistics was written in response to instructors who did not want a formula driven,mathematically encyclopedic book. The use of computer applications means some topics no longer require detailed coverage . This allows for new material,useful to a business manager,that solidifies the concepts and applications of statistics to business and economics. This book is unique because the examples include real data that relate to the functional areas of business such as finance,accounting,marketing. Formal probability is de-emphasized. The material is presented in a well-written,easy style designed to motivate students. The emphasis is on understandability and application as opposed to mathematical precision and formula detail.

Product Details

ISBN-13:	9780128111758
Publisher:	Elsevier Science & Technology Books
Publication date:	07/29/2016
Sold by:	Barnes & Noble
Format:	eBook
Pages:	642
File size:	44 MB
Note:	This product may take a few minutes to download.

About the Author

Andrew F. Siegel holds the Grant I. Butterbaugh Professorship in Quantitative Methods and Finance at the Michael G. Foster School of Business, University of Washington, Seattle, and is also Adjunct Professor in the Department of Statistics. His Ph.D. is in statistics from Stanford University (1977). Before settling in Seattle, he held teaching and/ or research positions at Harvard University, the University of Wisconsin, the RAND Corporation, the Smithsonian Institution, and Princeton University. He has taught statistics at both undergraduate and graduate levels, and earned seven teaching awards in 2015 and 2016. The interest-rate model he developed with Charles Nelson (the Nelson-Siegel Model) is in use at central banks around the world. His work has been translated into Chinese and Russian. His articles have appeared in many publications, including the Journal of the American Statistical Association, the Encyclopedia of Statistical Sciences, the American Statistician, Proceedings of the National Academy of Sciences, Nature, the American Mathematical Monthly, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Probability, the Society for Industrial and Applied Mathematics Journal on Scientific and Statistical Computing, Statistics in Medicine, Biometrika, Biometrics, Statistical Applications in Genetics and Molecular Biology, Mathematical Finance, Contemporary Accounting Research, the Journal of Finance, and the Journal of Applied Probability.

Michael R. Wagner is an Associate Professor of Operations Management and a Neal and Jan Dempsey Endowed Faculty Fellow at the Michael G. Foster School of Business, University of Washington, Seattle. His Ph.D. is in Operations Research from MIT (2006). He has taught data analytics at both undergraduate and graduate levels, and earned the Ron Crockett Award for Innovation in Education (2014). His articles have appeared in many publications, including the journals Management Science, Operations Research, Manufacturing & Service Operations Management, Mathematics of Operations Research, Mathematical Programming, IIE Transactions, European Journal of Operational Research, Operations Research Letters, Networks, Computers & Operations Research, and Transportation Science.

Table of Contents

Part I:Introduction :Defining The Role Of Statistics In Business
1.Introduction:Defining The Role Of Statistics In Business
2.Data Structures:Classifying The Various Types Of Data Sets
3.Histograms:Looking At The Distribution Of Data
4.Landmark Summaries:Interpreting Typical Values And Percentiles
5.Variabilty:Dealing With Diversity
Part Ii:Probabilty
6.Probability:Understanding Random Situations
7.Random Variables:Working With Uncertain Numbers
Part Iii:Statistical Inference
8.Random Sampling
9.Confidence Intervals:Admitting That Estimates Are Not Exact
10.Hypothesis Testing:Deciding Between Reality And Coincidence
Part Iv:Regression And Time Series
11.Correaltion And Regression:Measuring And Predicting Relationships
12.Multiple Regression:Predicting One Factor From Several Others
13.Report Writing:Communicating The Results Of A Multiple Regression
14.Time Series:Understanding Changes Over Time
Part V:Methods And Applications

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From the Publisher

Without getting bogged down in excessive mathematical details, this popular text employs an engaging and approachable style to teach fundamental business statistics principles and features helpful examples and exercises directly applicable to working professionals in finance, accounting, and marketing