Practical Business Statistics
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Practical Business Statistics

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Description

Practical Business Statistics, Seventh Edition, provides a conceptual, realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book provides deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This valuable, accessible approach teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results.

The text uses excellent examples with real world data relating to business sector functional areas such as finance, accounting, and marketing. Written in an engaging style, this timely revision is class-tested and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details.
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Product details

  • Paperback | 642 pages
  • 216 x 276 x 30.48mm | 1,630g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 7th edition
  • Illustrated; Illustrations, unspecified
  • 0128042508
  • 9780128042502

Table of contents

Part I: Introduction and Descriptive Statistics

Chapter 1: Introduction: Defining the Role of Statistics in Business

Chapter 2: Data Structures: Classifying the Various Types of Data Sets

Chapter 3: Histograms: Looking at the Distribution of Data

Chapter 4: Landmark Summaries: Interpreting Typical Values and Percentiles

Chapter 5: Variability: Dealing with Diversity

Part II: Probability

Chapter 6: Probability: Understanding Random Situations

Chapter 7: Random Variables: Working with Uncertain Numbers

Part III: Statistical Inference

Chapter 8: Random Sampling: Planning Ahead for Data Gathering

Chapter 9: Confidence Intervals: Admitting That Estimates Are Not Exact

Chapter 10: Hypothesis Testing: Deciding Between Reality and Coincidence

Part IV: Regression and Time Series

Chapter 11: Correlation and Regression: Measuring and Predicting Relationships

Chapter 12: Multiple Regression: Predicting One Variable From Several Others

Chapter 13: Report Writing: Communicating the Results of a Multiple Regression

Chapter 14: Time Series: Understanding Changes Over Time

Part V: Methods and Applications

Chapter 15: ANOVA: Testing for Differences Among Many Samples and Much More

Chapter 16: Nonparametrics: Testing with Ordinal Data or Nonnormal Distributions

Chapter 17: Chi-Squared Analysis: Testing for Patterns in Qualitative Data

Chapter 18: Quality Control: Recognizing and Managing Variation
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About Andrew Siegel

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.
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19 ratings
3.78 out of 5 stars
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2 11% (2)
1 5% (1)
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