| Applied Statistics for Business and Economics Contributor(s): Leekley, Robert M. (Author) |
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ISBN: 1439805687 ISBN-13: 9781439805688 Publisher: CRC Press OUR PRICE: $142.50 Product Type: Hardcover - Other Formats Published: April 2010 Annotation: Designed to impart a functional understanding of statistics, this text encourages the development of application and decision making skills for use in managing raw data and real-world projects. Concise and well-written, the text does not require calculus, instead making liberal use of spreadsheet software to facilitate the handling of larger, more relevant data sets. Integrated chapters follow a logical progression, often enabling the addition of topics that are less typical and more advanced, such as scattergrams and time series graphs, simple and multiple regressions, time series analysis, and random sampling. Eschewing a formulaic approach, the text instead provides the skills for meaningful management of raw data into actionable information. |
| Additional Information |
| BISAC Categories: - Business & Economics | Statistics - Business & Economics | Finance - General - Mathematics | Probability & Statistics - General |
| Dewey: 519.5 |
| LCCN: 2009044113 |
| Physical Information: 1.2" H x 7.1" W x 10" (2.25 lbs) 496 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Designed for a one-semester course, Applied Statistics for Business and Economics offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world. Numerous interesting and important examples reflect real-life situations, stimulating students to think realistically in tackling these problems. Calculations can be performed using any standard spreadsheet package. To help with the examples, the author offers both actual and hypothetical databases on his website http: //iwu.edu/ bleekley The text explores ways to describe data and the relationships found in data. It covers basic probability tools, Bayes' theorem, sampling, estimation, and confidence intervals. The text also discusses hypothesis testing for one and two samples, contingency tables, goodness-of-fit, analysis of variance, and population variances. In addition, the author develops the concepts behind the linear relationship between two numeric variables (simple regression) as well as the potentially nonlinear relationships among more than two variables (multiple regression). The final chapter introduces classical time-series analysis and how it applies to business and economics. This text provides a practical understanding of the value of statistics in the real world. After reading the book, students will be able to summarize data in insightful ways using charts, graphs, and summary statistics as well as make inferences from samples, especially about relationships. |