Business Statistics
John Wiley & Sons Inc (Verlag)
978-1-119-57762-1 (ISBN)
Preface vii
About the Authors xiii
Unit I Introduction
1 Introduction to Statistics and Business Analytics 1-1
Decision Dilemma: Statistics Describe the State of Business in India’s Countryside 1-1
Introduction 1-2
1.1 Basic Statistical Concepts 1-3
1.2 Variables, Data, and Data Measurement 1-5
Thinking Critically About Statistics in Business Today 1.1 1-6
1.3 Big Data 1-10
1.4 Business Analytics 1-12
1.5 Data Mining and Data Visualization 1-14
Decision Dilemma Solved 1-17
Key Considerations 1-17
Why Statistics is Relevant 1-17
Summary of Learning Objectives / Key Terms / Supplementary Problems / Exploring the Databases with Business Analytics Case: Canadian Farmers Dealing with Stress 1-20
Big Data Case 1-21
Using the Computer 1-21
2 Visualizing Data with Charts and Graphs 2-1
Decision Dilemma: Energy Consumption Around the World 2-1
Introduction 2-2
2.1 Frequency Distributions 2-3
2.2 Quantitative Data Graphs 2-7
2.3 Qualitative Data Graphs 2-12
Thinking Critically About Statistics in Business Today 2.1 2-13
2.4 Charts and Graphs for Two Variables 2-18
2.5 Visualizing Time-Series Data 2-22
Decision Dilemma Solved 2-26
Key Considerations 2-27
Why Statistics is Relevant 2-27
Summary of Learning Objectives / Key Terms /
Supplementary Problems / Exploring the Databases with Business Analytics Case: Southwest Airlines and WestJet Airlines Ltd. 2-33
Big Data Case 2-35
Using the Computer 2-35
3 Descriptive Statistics 3-1
Decision Dilemma: Laundry Statistics 3-1
Introduction 3-2
3.1 Measures of Central Tendency 3-2
3.2 Measures of Variability 3-10
Thinking Critically About Statistics in Business Today 3.1 3-11
Thinking Critically About Statistics in Business Today 3.2 3-22
3.3 Measures of Shape 3-24
3.4 Business Analytics Using Descriptive Statistics 3-29
Decision Dilemma Solved 3-31
Key Considerations 3-31
Why Statistics is Relevant 3-31
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Coca-Cola Develops the African Market 3-37
Big Data Case 3-38
Using the Computer 3-38
4 Probability 4-1
Decision Dilemma: Education, Gender, and Employment 4-1
Introduction 4-2
4.1 Introduction to Probability 4-2
4.2 Structure of Probability 4-5
4.3 Marginal, Union, Joint, and Conditional Probabilities 4-11
4.4 Addition Laws 4-13
4.5 Multiplication Laws 4-20
4.6 Conditional Probability 4-26
Thinking Critically About Statistics in Business Today 4.1 4-27
4.7 Revision of Probabilities: Bayes’ Rule 4-31
Decision Dilemma Solved 4-35
Key Considerations 4-36
Why Statistics is Relevant 4-36
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics
Case: Bluewater Recycling Association Offers Bigger Bins 4-41
Big Data Case 4-42
Unit II Distributions and Sampling
5 Discrete Distributions 5-1
Decision Dilemma: Life with a Cellphone 5-1
Introduction 5-2
5.1 Discrete Versus Continuous Distributions 5-2
5.2 Describing a Discrete Distribution 5-4
5.3 Binomial Distribution 5-8
Thinking Critically About Statistics in Business Today 5.1 5-11
5.4 Poisson Distribution 5-19
Thinking Critically About Statistics in Business Today 5.2 5-20
5.5 Hypergeometric Distribution 5-28
Decision Dilemma Solved 5-32
Key Considerations 5-33
Why Statistics is Relevant 5-33
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Whole Foods Market Grows Through Mergers and Acquisitions 5-38
Big Data Case 5-39
Using the Computer 5-39
6 Continuous Distributions 6-1
Decision Dilemma: CSX Corporation 6-1
Introduction 6-2
6.1 Uniform Distribution 6-2
6.2 Normal Distribution 6-6
Thinking Critically About Statistics in Business Today 6.1 6-6
6.3 Using the Normal Curve to Approximate Binomial Distribution Problems 6-17
6.4 Exponential Distribution 6-23
Decision Dilemma Solved 6-27
Key Considerations 6-28
Why Statistics is Relevant 6-28
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Mercedes Goes after Younger Buyers 6-33
Big Data Case 6-33
Using the Computer 6-34
7 Sampling and Sampling Distributions 7-1
Decision Dilemma: What is the Attitude of Maquiladora Workers? 7-1
Introduction 7-2
7.1 Sampling 7-2
Thinking Critically About Statistics in Business Today 7.1 7-9
7.2 Sampling Distribution of x¯ 7-14
7.3 Sampling Distribution of p 7-23
Decision Dilemma Solved 7-26
Key Considerations 7-26
Why Statistics is Relevant 7-26
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics
Case: 3M 7-30
Big Data Case 7-31
Using the Computer 7-31
Unit III Making Inferences About Population Parameters
8 Statistical Inference: Estimation for Single Populations 8-1
Decision Dilemma: Batteries and Bulbs: How Long Do They Last? 8-1
Introduction 8-2
8.1 Estimating the Population Mean Using the z Statistic (σ Known) 8-3
8.2 Estimating the Population Mean Using the t Statistic (σ Unknown) 8-10
Thinking Critically About Statistics in Business Today 8.1 8-10
8.3 Estimating the Population Proportion 8-16
Thinking Critically About Statistics in Business Today 8.2 8-16
8.4 Estimating the Population Variance 8-20
8.5 Estimating Sample Size 8-23
Decision Dilemma Solved 8-27
Key Considerations 8-28
Why Statistics is Relevant 8-28
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: The Container Store 8-32
Big Data Case 8-34
Using the Computer 8-34
9 Statistical Inference: Hypothesis Testing for Single Populations 9-1
Decision Dilemma: Business Referrals 9-1
Introduction 9-2
9.1 Introduction to Hypothesis Testing 9-3
9.2 Testing Hypotheses About a Population Mean Using the z Statistic (σ Known) 9-12
9.3 Testing Hypotheses About a Population Mean Using the t Statistic (σ Unknown) 9-19
9.4 Testing Hypotheses About a Proportion 9-25
Thinking Critically About Statistics in Business Today 9.1 9-25
9.5 Testing Hypotheses About a Variance 9-30
9.6 Solving for Type II Errors 9-33
Decision Dilemma Solved 9-40
Key Considerations 9-41
Why Statistics is Relevant 9-41
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: A&W’s New Menu Targets Meat Alternatives 9-46
Big Data Case 9-47
Using the Computer 9-47
10 Statistical Inferences About Two Populations 10-1
Decision Dilemma: L.L. Bean 10-1
Introduction 10-2
10.1 Hypothesis Testing and Confidence Intervals About the Difference in Two Means Using the z Statistic: Population Variances Known 10-4
10.2 Hypothesis Testing and Confidence Intervals About the Difference in Two Means Using the t Statistic: Independent Samples with Population Variances Unknown 10-12
Thinking Critically About Statistics in Business Today 10.1 10-13
10.3 Statistical Inferences for Two Related Populations 10-22
10.4 Statistical Inferences About Two Population Proportions, p1 − p2 10-31
10.5 Testing Hypotheses About Two Population Variances 10-37
Decision Dilemma Solved 10-44
Key Considerations 10-45
Why Statistics is Relevant 10-45
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics
Case: Seitz LLC: Producing Quality Gear-Driven and Linear-Motion Products 10-52
Big Data Case 10-53
Using the Computer 10-53
11 Analysis of Variance and Design of Experiments 11-1
Decision Dilemma: Job and Career Satisfaction of Foreign Self-Initiated Expatriates 11-1
Introduction 11-2
11.1 Introduction to Design of Experiments 11-3
11.2 The Completely Randomized Design (One-Way ANOVA) 11-5
Thinking Critically About Statistics in Business Today 11.1 11-6
11.3 Multiple Comparison Tests 11-16
11.4 The Randomized Block Design 11-24
11.5 A Factorial Design (Two-Way ANOVA) 11-33
Decision Dilemma Solved 11-45
Key Considerations 11-46
Why Statistics is Relevant 11-46
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: ASCO Valve Canada’s RedHat Valve 11-52
Big Data Case 11-53
Using the Computer 11-54
Unit IV Regression Analysis and Forecasting
12 Correlation and Simple Regression Analysis 12-1
Decision Dilemma: Predicting International Hourly Wages by the Price of a Big MacTM 12-1
Introduction 12-2
12.1 Correlation 12-2
Thinking Critically About Statistics in Business Today 12.1 12-4
12.2 Introduction to Simple Regression Analysis 12-6
12.3 Determining the Equation of the Regression Line 12-8
12.4 Residual Analysis 12-14
12.5 Standard Error of the Estimate 12-21
12.6 Coefficient of Determination 12-24
12.7 Hypothesis Tests for the Slope of the Regression Model and for the Overall Model 12-27
12.8 Estimation 12-32
12.9 Using Regression to Develop a Forecasting Trend Line 12-36
12.10 Interpreting the Output 12-42
Decision Dilemma Solved 12-43
Key Considerations 12-43
Why Statistics is Relevant 12-44
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Caterpillar, Inc. 12-50
Big Data Case 12-51
Using the Computer 12-52
13 Multiple Regression Analysis 13-1
Decision Dilemma: Will You Like Your New Job? 13-1
Introduction 13-2
13.1 The Multiple Regression Model 13-2
13.2 Significance Tests of the Regression Model and Its Coefficients 13-10
13.3 Residuals, Standard Error of the Estimate, and R2 13-14
Thinking Critically About Statistics in Business Today 13.1 13-14
13.4 Interpreting Multiple Regression Computer Output 13-20
13.5 Using Regression Analysis: Some Caveats 13-23
Decision Dilemma Solved 13-27
Key Considerations 13-28
Why Statistics is Relevant 13-28
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Starbucks Introduces Debit Card 13-32
Big Data Case 13-34
Using the Computer 13-34
14 Building Multiple Regression Models 14-1
Decision Dilemma: Predicting CEO Salaries 14-1
14.1 Nonlinear Models: Mathematical Transformation 14-2
Thinking Critically About Statistics in Business Today 14.1 14-4
14.2 Indicator (Dummy) Variables 14-16
14.3 Model Building: Search Procedures 14-21
14.4 Multicollinearity 14-31
14.5 Logistic Regression 14-34
Decision Dilemma Solved 14-41
Key Considerations 14-41
Why Statistics is Relevant 14-42
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Ceapro Turns Oats into Beneficial Products 14-48
Big Data Case 14-49
Using the Computer 14-49
15 Time-Series Forecasting and Index Numbers 15-1
Decision Dilemma: Forecasting Air Pollution 15-1
Introduction 15-2
15.1 Introduction to Forecasting 15-2
15.2 Smoothing Techniques 15-7
15.3 Trend Analysis 15-17
Thinking Critically About Statistics In Business Today 15.1 15-17
15.4 Seasonal Effects 15-24
15.5 Autocorrelation and Autoregression 15-29
15.6 Index Numbers 15-36
Decision Dilemma Solved 15-42
Key Considerations 15-45
Why Statistics is Relevant 15-45
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Dofasco Changes Its Style 15-52
Big Data Case 15-53
Using the Computer 15-53
Unit V Special Topics
16 A nalysis of Categorical Data 16-1
Decision Dilemma: Selecting Suppliers in the Electronics Industry 16-1
Introduction 16-2
16.1 Chi-Square Goodness-of-Fit Test 16-2
16.2 Contingency Analysis: Chi-Square Test of Independence 16-9
Thinking Critically About Statistics in Business Today 16.1 16-10
Decision Dilemma Solved 16-16
Key Considerations 16-16
Why Statistics is Relevant 16-17
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Foot Locker in the Shoe Mix 16-20
Big Data Case 16-21
Using the Computer 16-21
17 Nonparametric Statistics 17-1
Decision Dilemma: How is the Doughnut Business Doing? 17-1
Introduction 17-2
17.1 Runs Test 17-3
17.2 Mann-Whitney U Test 17-8
Thinking Critically About Statistics in Business Today 17.1 17-8
17.3 Wilcoxon Matched-Pairs Signed Rank Test 17-16
17.4 Kruskal-Wallis Test 17-23
17.5 Friedman Test 17-27
17.6 Spearman’s Rank Correlation 17-32
Decision Dilemma Solved 17-36
Key Considerations 17-37
Why Statistics is Relevant 17-37
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Schwinn 17-43
Big Data Case 17-44
Using the Computer 17-45
18 Statistical Quality Control 18-1
Decision Dilemma: Italy’s Piaggio Makes a Comeback 18-1
Introduction 18-2
18.1 Introduction to Quality Control 18-2
Thinking Critically About Statistics in Business Today 18.1 18-7
18.2 Process Analysis 18-12
18.3 Control Charts 18-18
Decision Dilemma Solved 18-32
Key Considerations 18-32
Why Statistics is Relevant 18-33
Summary of Learning Objectives / Key Terms / Formulas / Supplementary Problems / Exploring the Databases with Business Analytics Case: Catalyst Paper Introduces Microsoft Dynamics CRM 18-38
Big Data Case 18-39
19 Decision Analysis 19-1
Decision Dilemma: Decision-Making at the CEO Level 19-1
Introduction 19-2
19.1 The Decision Table and Decision-Making Under Certainty 19-3
19.2 Decision-Making Under Uncertainty 19-5
Thinking Critically About Statistics in Business Today 19.1 19-5
19.3 Decision-Making Under Risk 19-13
19.4 Revising Probabilities in Light of Sample Information 19-21
Decision Dilemma Solved 19-29
Key Considerations 19-30
Why Statistics is Relevant 19-30
Summary of Learning Objectives / Key Terms / Formula / Supplementary Problems / Exploring the Databases with Business Analytics Case: Fletcher-Terry: On the Cutting Edge 19-34
Big Data Case 19-35
Appendix A Tables A-1
Appendix B Making Inferences About Population Parameters: A Brief Summary B-1
Appendix C Answers to Selected Odd-Numbered Quantitative Problems C-1
Glossary G-1
Index I-1
Erscheinungsdatum | 16.09.2020 |
---|---|
Verlagsort | New York |
Sprache | englisch |
Maße | 216 x 277 mm |
Gewicht | 1658 g |
Themenwelt | Wirtschaft ► Betriebswirtschaft / Management |
ISBN-10 | 1-119-57762-4 / 1119577624 |
ISBN-13 | 978-1-119-57762-1 / 9781119577621 |
Zustand | Neuware |
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