Practical Business Statistics, Instructor Solutions Manual (e-only)
- 1st Edition - April 15, 2011
- Latest edition
- Author: Andrew F. Siegel
- Language: English
Practical Business Statistics is a conceptual and definitive guide to managerial statistics that masterfully maintains mathematical correctness. The book aims to help users learn… Read more
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Practical Business Statistics is a conceptual and definitive guide to managerial statistics that masterfully maintains mathematical correctness. The book aims to help users learn to analyze and process data with uncertainty, while encouraging readers to use practical computer applications. The book is divided into 18 chapters, all of which follow a uniform presentation outline: starting with an overview that explains why the subject matter is important to business and concluding with a comprehensive summary, with keywords, questions, problems, database exercises and projects. The book features the following concepts of business statistics: o The role of statistics in business o Classification of data sets o Interpretation of typical values and percentiles o Variability and probability o Working with uncertain numbers o Random sampling o Confidence intervals o Hypothesis testing o Correlation and regression o Time series o ANOVA o Ordinal data and non-normal distributions o Chi-square and managing variations The book presents information in a lively, user -friendly style, while maintaining technical accuracy. The text also features excellent examples with real-world data relating to the functional areas of business: finance, accounting, and marketing. Students in business and management statistics courses, quantitative methods in management, and analytics will find this book an excellent reference for learning. Business managers and lecturers will also find this book invaluable.
Preface1. Introduction: Defining the Role of Statistics in Business2. Data Structures: Classifying the Various Types of Data Sets 3. Histograms: Looking at the Distribution of the Data4. Landmark Summaries: Interpreting Typical Values and Percentiles 5. Variability: Dealing with Diversity 6. Probability: Understanding Random Situations 7. Random Variables: Working with Uncertain Numbers 8. Random Sampling: Planning Ahead for Data Gathering 9. Confidence Intervals: Admitting that Estimates are not Exact 10. Hypothesis Testing: Deciding between Reality and Coincidence11. Correlation and Regression: Measuring and Predicting Relationships 12. Multiple Regression: Predicting One Variable from Several Others 13. Report Writing: Communicating the Results of a Multiple Regression 14. Time Series: Understanding Changes Over Time15. ANOVA: Testing for Differences among Many Samples, and Much More 16. Nonparametrics: Testing with Ordinal Data or Nonnormal Distributions17. Chi-Squared Analysis: Testing for Patterns in Qualitative Data18. Quality Control: Recognizing and Managing Variation
- Edition: 1
- Latest edition
- Published: April 15, 2011
- Language: English
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Andrew F. 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.
Affiliations and expertise
Professor of Information Systems and Operations Management, Professor of Finance and Business Economics, and Adjunct Professor of Statistics, Foster School of Business, University of Washington, Seattle, WA, USA