Concise Managerial Statistics

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Cengage Learning, Mar 18, 2005 - Business & Economics - 656 pages
Get the grade you need and prepare for the business world with CONCISE MANAGERIAL STATISTICS. Learn Business Statistics without the complicated math. Fully integrating the use of computers with statistics, the textbook describes the concepts and applications of business statistics and gives you an opportunity to observe and actually carry out computer-generated solutions using SPSS, Microsoft Excel, and MINITAB. Plus, this volume comes with access to InfoTrac College Edition! Save time, save money--and eliminate the trek to the library and long waits for reserved readings with this online university library of more than 5,000 academic and popular magazines, newspapers, and journals.
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Contents

Data Presentation Using Descriptive Graphs
Data Summary Using Descriptive Measures
Probability Concepts
Discrete Probability Distributions
Continuous Probability Distributions
Statistical Inference and Sampling
Hypothesis Testing for the Mean of a Population
Comparing Two or More Populations
Analysis of Categorical Data
Correlation and Simple Linear Regression
Multiple Linear Regression
Time Series Analysis and Forecasting
Appendixes
Index
Copyright

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About the author (2005)

Al Kvanli is Associate Professor of Management Science and Statistics at the University of North Texas. He received the MA degree in mathematics from the University of Kansas and the Ph.D. in mathematical statistics from Southern Methodist University. For the past fifteen years Dr. Kvanli has been the statistical consultant for the Department of Health and Human Services (HHS), Office of Audit. In this role, he created much of the statistical software used by federal auditors and teaches sampling courses for state and federal auditors. He often serves as expert witness in appeals of monetary recovery by HHS and he has written a number of articles related to the application of statistical sampling in an audit environment.

Robert Pavur is Professor of Management Science and Statistics at the University of North Texas. He received the Ph.D. in statistics from Texas Tech University. He has held various officer positions, including president, in the Southwest regional Decision Science Institute and received its distinguished service award in 2000. He has published a number of articles on alternative approaches to solving the statistical classification problem. His papers have appeared in journals such as the Annals of Operations Research, IEEE Transactions on Reliability, European Journal of Operational Research, Journal of the Operational Research Society, and International Journal of Operations and Quantitative Management. He uses his statistical skills as a cryptologist in the Naval Reserve.

Kellie B. Keeling is an Assistant Professor of Business Information Technology at Virginia Tech. She received the Ph.D. in Management Science from the University of North Texas and the M.B.A. and B.S. in Mathematics from Wayland Baptist University. She has taught statistics, operations management, and simulation courses. Dr. Keeling has received the R. B. Pamplin College of Business Certificate of Teaching Excellence and the Virginia Tech University Certificate of Teaching Excellence.

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