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An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more stream-lined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author--an expert in the field--offers…mehr
An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more stream-lined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author--an expert in the field--offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are intro-duced through examples, and the text is designed to be accessible to readers with a variety of backgrounds. To enhance learning, most of the mathematical formulae and notation appears in technical appendices at the end of each chapter. This important resource: * Offers a comprehensive guide to understanding business statistics targeting business and economics students and professionals * Introduces the concepts and techniques through concise and intuitive examples * Focuses on understanding by moving distracting formulae and mathematical notation to appendices * Offers intuition, insights, humor, and practical advice for students of business statistics * Features coverage of sampling techniques, descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis tests, and regression Written for undergraduate business students, business and economics majors, teachers, and practitioners, A Guide to Business Statistics offers an accessible guide to the key concepts and fundamental principles in statistics.
DAVID M. MCEVOY, PHD, is an Associate Professor in the Economics Department at Appalachian State University in Boone NC. He has published over 20 peer-reviewed articles and is coeditor of two books. Dr. McEvoy is an award-winning educator who has taught undergraduate courses in business statistics for over 10 years.
Inhaltsangabe
Dedication Preface 0.1. Addressing two challenges 0.2. How to use this book 0.3. Target audience Chapter 1: Types of Data 1.1. Categorical data 1.2. Numerical data 1.3. Level of measurement 1.4. Cross-sectional, time-series and panel data 1.5. Summary Chapter 2: Populations and Samples 2.1. What is the population of interest? 2.2. How to sample from a population? 2.3. Getting the data 2.4. Summary Chapter 3: Descriptive Statistics 3.1. Measures of central tendency 3.2. Measures of variability 3.3. The shape 3.4. Summary Technical Appendix Chapter 4: Probability 4.1. Simple probabilities 4.2. Empirical probabilities 4.3. Conditional probabilities 4.4. Summary Technical Appendix Chapter 5: The Normal Distribution 5.1. The bell shape 5.2. The Empirical Rule 5.3. Standard normal distribution 5.4. Normal approximations 5.5. Summary Technical Appendix Chapter 6: Sampling Distributions 6.1. Defining a sampling distribution 6.2. The importance of sampling distributions 6.3. An example of a sampling distribution 6.4. Characteristics of a sampling distribution of a mean 6.5. Sampling distribution of a proportion 6.6. Summary Technical Appendix Chapter 7: Confidence Intervals 7.1. Confidence intervals for means 7.2. Confidence intervals for proportions 7.3. Sample size and the width of confidence intervals 7.4. Comparing two proportions from the same poll 7.5. Summary Technical Appendix Chapter 8: Hypothesis Tests of a Population Mean 8.1. Two-tail hypothesis test of a mean 8.2. One-tail hypothesis test of a mean 8.3. p-value approach to hypothesis tests 8.4. Summary Technical Appendix Chapter 9: Hypothesis Tests of Categorical Data 9.1. Two-tail hypothesis test of a proportion 9.2. One-tail hypothesis test of a proportion 9.3. Using p-values 9.4. Chi-square tests 9.5. Summary Technical Appendix Chapter 10: Hypothesis Tests Comparing Two Parameters 10.1. The approach in this chapter 10.2. Hypothesis tests of two means 10.3. Hypothesis tests of two variances 10.4. Hypothesis tests of two proportions 10.5. Summary Technical Appendix Chapter 11: Simple Linear Regression 11.1. The population regression model 11.2. A look at the data 11.3. Ordinary Least Squares (OLS) 11.4. The distribution of b0 and b1 11.5. Tests of significance 11.6. Goodness of fit 11.7. Checking for violations of the assumptions 11.8. Summary Technical Appendix Chapter 12: Multiple Regression 12.1. Population regression model 12.2. The data 12.3. Sample regression function 12.4. Interpreting the estimates 12.5. Prediction 12.6. Tests of significance 12.7. Goodness of fit 12.8. Multicollinearity 12.9. Summary Technical Appendix Chapter 13: More Topics in Regression 13.1. Hypothesis tests comparing two means with regression 13.2. Hypothesis tests comparing more than two means (ANOVA) 13.3. Interacting variables 13.4. Non-linearities 13.5. Time-series analysis 13.6. Summary Index
Preface xiii
1 Types of Data 1
1.1 Categorical Data 2
1.2 Numerical Data 3
1.3 Level of Measurement 4
1.4 Cross-Sectional, Time-Series, and Panel Data 5
1.5 Summary 7
2 Populations and Samples 9
2.1 What is the Population of Interest? 10
2.2 How to Sample From a Population? 11
2.2.1 Simple Random Sampling 11
2.2.2 Stratified Sampling 14
2.2.3 Other Methods 15
2.3 Getting the Data 16
2.4 Summary 17
3 Descriptive Statistics 19
3.1 Measures of Central Tendency 20
3.1.1 The Mean 20
3.1.2 The Median 23
3.1.3 The Mode 24
3.2 Measures of Variability 24
3.2.1 Variance and Standard Deviation 24
3.3 The Shape 26
3.4 Summary 28
Technical Appendix 29
4 Probability 31
4.1 Simple Probabilities 32
4.1.1 When to Add Probabilities Together 34
4.1.2 When to Find Intersections 36
4.2 Empirical Probabilities 37
4.3 Conditional Probabilities 39
4.4 Summary 41
Technical Appendix 42
5 The Normal Distribution 43
5.1 The Bell Shape 43
5.2 The Empirical Rule 44
5.3 Standard Normal Distribution 46
5.3.1 Probabilities with Continuous Distributions 48
5.3.2 Verifying the Empirical Rule Using the z-table 48
5.4 Normal Approximations 48
5.4.1 Mean 49
5.4.2 Standard deviation 49
5.4.3 Shape 50
5.5 Summary 51
Technical Appendix 52
6 Sampling Distributions 55
6.1 Defining a Sampling Distribution 55
6.2 The Importance of Sampling Distributions 56
6.3 An Example of a Sampling Distribution 57
6.4 Characteristics of a Sampling Distribution of a Mean 61
6.4.1 The Mean 61
6.4.2 The Shape 62
6.4.3 The Standard Deviation 64
6.4.4 Finding Probabilities With a Sampling Distribution 65
6.5 Sampling Distribution of a Proportion 67
6.5.1 The Mean 68
6.5.2 The Shape 68
6.5.3 The Standard Deviation 68
6.6 Summary 70
Technical Appendix 71
7 Confidence Intervals 73
7.1 Confidence Intervals for Means 74
7.1.1 The Characteristics of the Sampling Distribution 75
7.1.2 Confidence Intervals Using the z-Distribution 76
7.1.3 Confidence Intervals Using the t-Distribution 78
7.2 Confidence Intervals for Proportions 80
7.3 Sample Size and theWidth of Confidence Intervals 81
7.4 Comparing Two Proportions From the Same Poll 82
7.5 Summary 84
Technical Appendix 85
8 Hypothesis Tests of a Population Mean 89
8.1 Two-Tail Hypothesis Test of a Mean 90
8.1.1 A Single Sample from a Population 90
8.1.2 Setting Up the Null and Alternative Hypothesis 92
8.1.3 Decisions and Errors 92
8.1.4 Rejection Regions and Conclusions 94
8.1.5 Changing the Level of Significance 95
8.2 One-Tail Hypothesis Test of a Mean 97
8.2.1 Setting Up the Null and Alternative Hypotheses 97
Dedication Preface 0.1. Addressing two challenges 0.2. How to use this book 0.3. Target audience Chapter 1: Types of Data 1.1. Categorical data 1.2. Numerical data 1.3. Level of measurement 1.4. Cross-sectional, time-series and panel data 1.5. Summary Chapter 2: Populations and Samples 2.1. What is the population of interest? 2.2. How to sample from a population? 2.3. Getting the data 2.4. Summary Chapter 3: Descriptive Statistics 3.1. Measures of central tendency 3.2. Measures of variability 3.3. The shape 3.4. Summary Technical Appendix Chapter 4: Probability 4.1. Simple probabilities 4.2. Empirical probabilities 4.3. Conditional probabilities 4.4. Summary Technical Appendix Chapter 5: The Normal Distribution 5.1. The bell shape 5.2. The Empirical Rule 5.3. Standard normal distribution 5.4. Normal approximations 5.5. Summary Technical Appendix Chapter 6: Sampling Distributions 6.1. Defining a sampling distribution 6.2. The importance of sampling distributions 6.3. An example of a sampling distribution 6.4. Characteristics of a sampling distribution of a mean 6.5. Sampling distribution of a proportion 6.6. Summary Technical Appendix Chapter 7: Confidence Intervals 7.1. Confidence intervals for means 7.2. Confidence intervals for proportions 7.3. Sample size and the width of confidence intervals 7.4. Comparing two proportions from the same poll 7.5. Summary Technical Appendix Chapter 8: Hypothesis Tests of a Population Mean 8.1. Two-tail hypothesis test of a mean 8.2. One-tail hypothesis test of a mean 8.3. p-value approach to hypothesis tests 8.4. Summary Technical Appendix Chapter 9: Hypothesis Tests of Categorical Data 9.1. Two-tail hypothesis test of a proportion 9.2. One-tail hypothesis test of a proportion 9.3. Using p-values 9.4. Chi-square tests 9.5. Summary Technical Appendix Chapter 10: Hypothesis Tests Comparing Two Parameters 10.1. The approach in this chapter 10.2. Hypothesis tests of two means 10.3. Hypothesis tests of two variances 10.4. Hypothesis tests of two proportions 10.5. Summary Technical Appendix Chapter 11: Simple Linear Regression 11.1. The population regression model 11.2. A look at the data 11.3. Ordinary Least Squares (OLS) 11.4. The distribution of b0 and b1 11.5. Tests of significance 11.6. Goodness of fit 11.7. Checking for violations of the assumptions 11.8. Summary Technical Appendix Chapter 12: Multiple Regression 12.1. Population regression model 12.2. The data 12.3. Sample regression function 12.4. Interpreting the estimates 12.5. Prediction 12.6. Tests of significance 12.7. Goodness of fit 12.8. Multicollinearity 12.9. Summary Technical Appendix Chapter 13: More Topics in Regression 13.1. Hypothesis tests comparing two means with regression 13.2. Hypothesis tests comparing more than two means (ANOVA) 13.3. Interacting variables 13.4. Non-linearities 13.5. Time-series analysis 13.6. Summary Index
Preface xiii
1 Types of Data 1
1.1 Categorical Data 2
1.2 Numerical Data 3
1.3 Level of Measurement 4
1.4 Cross-Sectional, Time-Series, and Panel Data 5
1.5 Summary 7
2 Populations and Samples 9
2.1 What is the Population of Interest? 10
2.2 How to Sample From a Population? 11
2.2.1 Simple Random Sampling 11
2.2.2 Stratified Sampling 14
2.2.3 Other Methods 15
2.3 Getting the Data 16
2.4 Summary 17
3 Descriptive Statistics 19
3.1 Measures of Central Tendency 20
3.1.1 The Mean 20
3.1.2 The Median 23
3.1.3 The Mode 24
3.2 Measures of Variability 24
3.2.1 Variance and Standard Deviation 24
3.3 The Shape 26
3.4 Summary 28
Technical Appendix 29
4 Probability 31
4.1 Simple Probabilities 32
4.1.1 When to Add Probabilities Together 34
4.1.2 When to Find Intersections 36
4.2 Empirical Probabilities 37
4.3 Conditional Probabilities 39
4.4 Summary 41
Technical Appendix 42
5 The Normal Distribution 43
5.1 The Bell Shape 43
5.2 The Empirical Rule 44
5.3 Standard Normal Distribution 46
5.3.1 Probabilities with Continuous Distributions 48
5.3.2 Verifying the Empirical Rule Using the z-table 48
5.4 Normal Approximations 48
5.4.1 Mean 49
5.4.2 Standard deviation 49
5.4.3 Shape 50
5.5 Summary 51
Technical Appendix 52
6 Sampling Distributions 55
6.1 Defining a Sampling Distribution 55
6.2 The Importance of Sampling Distributions 56
6.3 An Example of a Sampling Distribution 57
6.4 Characteristics of a Sampling Distribution of a Mean 61
6.4.1 The Mean 61
6.4.2 The Shape 62
6.4.3 The Standard Deviation 64
6.4.4 Finding Probabilities With a Sampling Distribution 65
6.5 Sampling Distribution of a Proportion 67
6.5.1 The Mean 68
6.5.2 The Shape 68
6.5.3 The Standard Deviation 68
6.6 Summary 70
Technical Appendix 71
7 Confidence Intervals 73
7.1 Confidence Intervals for Means 74
7.1.1 The Characteristics of the Sampling Distribution 75
7.1.2 Confidence Intervals Using the z-Distribution 76
7.1.3 Confidence Intervals Using the t-Distribution 78
7.2 Confidence Intervals for Proportions 80
7.3 Sample Size and theWidth of Confidence Intervals 81
7.4 Comparing Two Proportions From the Same Poll 82
7.5 Summary 84
Technical Appendix 85
8 Hypothesis Tests of a Population Mean 89
8.1 Two-Tail Hypothesis Test of a Mean 90
8.1.1 A Single Sample from a Population 90
8.1.2 Setting Up the Null and Alternative Hypothesis 92
8.1.3 Decisions and Errors 92
8.1.4 Rejection Regions and Conclusions 94
8.1.5 Changing the Level of Significance 95
8.2 One-Tail Hypothesis Test of a Mean 97
8.2.1 Setting Up the Null and Alternative Hypotheses 97
8.2.2 Rejection Regions and Conclusions 98
8.3 p-Value Approach to Hypothesis Tests 99
8.3.1 One-Tail Tests 99
8.3.2 Two-tail tests 100
8.4 Summary 100
Technical Appendix 101
9 Hypothesis Tests of Categorical Data 103
9.1 Two-Tail Hypothesis Test of a Proportion 104
9.1.1 A Single Sample from a Population 104
9.1.2
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