|Statistics for Management||
Statistics for Management
|102.00||approx. 7-9 days|
Appropriate for one or two term courses in introductory Business Statistics. With Statistics for Management, Levin and Rubin have provided a non-intimidating business statistics textbook that students can easily read and understand. Like its predecessors, the Seventh Edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the text an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how textbook principles work in professional practice.
Sampling distributions. Pg.___
Relationship between confidence level and confidence interval. Pg.___
Interpreting “r-square”. Pg.___
Chapter review exercises.
Chapter concepts tests.
“Statistics at Work” conceptual cases. Pg.___
“Computer Database Exercises. Pg.___
“From the Textbook to the Real-World Examples”. Pg.___
Chapter learning objectives.
Assumptions and hints boxes.
Chapter-opening problems (worked later in chapter).
Equations introduced and explained sections.
Explanation of the Poisson distribution. Pg.___
Standard error of the difference between two means. Pg.___
Explanation and decomposition of deviation. Pg.___
In-chapter exercises (both basic and applications- oriented).
Self-check exercises with worked out answers in each section.
End-of-chapter review exercises with each chapter.
Real-world exercises in each chapter.
Chapter concepts test exercises in each chapter.
2. Grouping and Displaying Data to Convey Meaning: Tables and Graphs.
3. Measures of Central Tendency and Dispersion in Frequency Distributions.
4. Probability I: Introductory Ideas.
5. Probability Distributions.
6. Sampling and Sampling Distributions.
8. Testing Hypotheses: One Sample Tests.
9. Testing Hypotheses: Two-Sample Tests.
10. Quality and Quality Control.
11. Chi-Square and Analysis of Variance.
12. Simple Regression and Correlation.
13. Multiple Regression and Modeling.
14. Nonparametric Methods.
15. Time Series and Forecasting.
16. Index Numbers.
17. Decision Theory.