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In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania's Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely.
In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel ® 2010 and the XLSTAT TM add-in.
The MyStatLab TM course management system includes increased exercise coverage with the Second Edition , along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use.
Contenu
Preface
Index of Application
PART ONE: VARIATION
1. Introduction
1.1 What Is Statistics?
1.2 Previews
2. Data
2.1 Data Tables
2.2 Categorical and Numerical Data
2.3 Recoding and Aggregation
2.4 Time Series
2.5 Further Attributes of Data
Chapter Summary
3. Describing Categorical Data
3.1 Looking at Data
3.2 Charts of Categorical Data
3.3 The Area Principle
3.4 Mode and Median
Chapter Summary
4. Describing Numerical Data
4.1 Summaries of Numerical Variables
4.2 Histograms
4.3 Boxplot
4.4 Shape of a Distribution
4.5 Epilog
Chapter Summary
5. Association between Categorical Variables
5.1 Contingency Tables
5.2 Lurking Variables and Simpson's Paradox
5.3 Strength of Association
Chapter Summary
6. Association between Quantitative Variables
6.1 Scatterplots
6.2 Association in Scatterplots
6.3 Measuring Association
6.4 Summarizing Association with a Line
6.5 Spurious Correlation
Chapter Summary
Statistics in Action: Financial Time Series
Statistics in Action: Executive Compensation
PART TWO: PROBABILITY
7. Probability
7.1 From Data to Probability
7.2 Rules for Probability
7.3 Independent Events
Chapter Summary
8. Conditional Probability
8.1 From Tables to Probabilities
8.2 Dependent Events
8.3 O rganizing Probabilities
8.4 O rder in Conditional Probabilities
Chapter Summary
9. Random Variables
9.1 Random Variables
9.2 Properties of Random Variables
9.3 Properties of Expected Values
9.4 Comparing Random Variables
Chapter Summary
10. Association between Random Variables
10.1 Portfolios and Random Variables
10.2 Joint Probability Distribution
10.3 Sums of Random Variables
10.4 Dependence between Random Variables
10.5 IID Random Variables
10.6 Weighted Sums
Chapter Summary
11. Probability Models for Counts
11.1 Random Variables for Counts
11.2 Binomial Model
11.3 Properties of Binomial Random Variables
11.4 Poisson Model
Chapter Summary
12. The Normal Probability Model
12.1 Normal Random Variable
12.2 The Normal Model
12.3 Percentiles
12.4 Departures from Normality
Chapter Summary
Statistics in Action: Managing Financial Risk
Statistics in Action: Modeling Sampling Variation
PART THREE: INFERENCE
13. Samples and Surveys
13.1 Two Surprising Properties of Samples
13.2 Variation
13.3 Alternative Sampling Methods
13.4 Questions to Ask
Chapter Summary
14. Sampling Variation and Quality
14.1 Sampling Distribution of the Mean
14.2 Control Limits
14.3 Using a Control Chart
14.4 Control Charts for Variation
Chapter Summary
15. Confidence Intervals
15.1 Ranges for Parameters
15.2 Confidence Interval for the Mean
15.3 Interpreting Confidence Intervals
15.4 Manipulating Confidence Intervals
15.5 Margin of Error
Chapter Summary
16. Statistical Tests
16.1 Concepts of Statistical Tests
16.2 Testing the Proportion
16.3 Testing the Mean
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