Statistics for Business: Pearson New International Edition
Autor Robert A. Stine, Dean Fosteren Limba Engleză Paperback – 27 sep 2019
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Specificații
ISBN-13: 9781292023397
ISBN-10: 1292023392
Pagini: 944
Dimensiuni: 217 x 277 x 43 mm
Greutate: 1.98 kg
Ediția:2nd edition
Editura: Pearson
Colecția Pearson Higher Education
ISBN-10: 1292023392
Pagini: 944
Dimensiuni: 217 x 277 x 43 mm
Greutate: 1.98 kg
Ediția:2nd edition
Editura: Pearson
Colecția Pearson Higher Education
Cuprins
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
1
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
1