Concise Managerial Statistics, International Edition (with CD-ROM and InfoTrac)
Published on 1. April 2005
Book
Mixed media product
656 pages
978-0-324-31445-8 (ISBN)
Description
The book is a higher-level introduction to Business Statistics text designed for use in a one-term course. It fully integrates the use of computers with statistics, by describing the concepts and applications of business statistics while giving users the opportunity to observe and actually carry out computer-generated solutions using SPSS, Microsoft (R) Excel, and MINITAB. Detailed how-to information for all three types of software is provided in the chapter appendices.
Professors who teach a one-term course and prefer to use higher-level problems will find this textbook is a perfect fit for their needs. The appropriate KPK Excel Macros (add-ins) that authors Pavur and Keeling have created may be used within the new book, expanding Excel's power in both graphing and regression analysis. The macros are built into the book's topical presentation, for even easier classroom integration.
Professors who teach a one-term course and prefer to use higher-level problems will find this textbook is a perfect fit for their needs. The appropriate KPK Excel Macros (add-ins) that authors Pavur and Keeling have created may be used within the new book, expanding Excel's power in both graphing and regression analysis. The macros are built into the book's topical presentation, for even easier classroom integration.
Reviews / Votes
1. A First Look at Statistics and Data Collection. 2. Data Presentation Using Descriptive Graphs. 3. Data Summary Using Descriptive Measures. 4. Probability Concepts. 5. Discrete Probability Distributions. 6. Continuous Probability Distributions. 7. Statistical Inference and Sampling. 8. Hypothesis Testing for the Mean of a Population. 9. Comparing Two or More Populations. 10. Analysis of Categorical Data. 11. Correlation and Simple Linear Regression. 12. Multiple Linear Regression. 13. Time series Analysis and Forecasting (on CD).More details
Edition
International ed
Language
English
Place of publication
Mason, OH
United States
Publishing group
Cengage Learning, Inc
Target group
College/higher education
Dimensions
Height: 246 mm
Width: 200 mm
Thickness: 25 mm
Weight
1158 gr
ISBN-13
978-0-324-31445-8 (9780324314458)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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. 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.
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. 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.
Content
1. A First Look at Statistics and Data Collection.
2. Data Presentation Using Descriptive Graphs.
3. Data Summary Using Descriptive Measures.
4. Probability Concepts.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Statistical Inference and Sampling.
8. Hypothesis Testing for the Mean of a Population.
9. Comparing Two or More Populations.
10. Analysis of Categorical Data.
11. Correlation and Simple Linear Regression.
12. Multiple Linear Regression.
13. Time series Analysis and Forecasting (on CD).
2. Data Presentation Using Descriptive Graphs.
3. Data Summary Using Descriptive Measures.
4. Probability Concepts.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Statistical Inference and Sampling.
8. Hypothesis Testing for the Mean of a Population.
9. Comparing Two or More Populations.
10. Analysis of Categorical Data.
11. Correlation and Simple Linear Regression.
12. Multiple Linear Regression.
13. Time series Analysis and Forecasting (on CD).