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A Guide to Business Statistics

Book Description

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 stream­lined 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 intro­duced 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.

 

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.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 streamlined 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 introduced through examples, and the text is designed to be accessible

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Preface
    1. Addressing Two Challenges
    2. How to Use This Book
    3. Target Audience
  6. Chapter 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. Chapter 2: Populations and Samples
    1. 2.1 What is the Population of Interest?
    2. 2.2 How to Sample From a Population?
    3. 2.3 Getting the Data
    4. 2.4 Summary
  8. Chapter 3: Descriptive Statistics
    1. 3.1 Measures of Central Tendency
    2. 3.2 Measures of Variability
    3. 3.3 The Shape
    4. 3.4 Summary
    5. Technical Appendix
  9. Chapter 4: Probability
    1. 4.1 Simple Probabilities
    2. 4.3 Conditional Probabilities
    3. 4.4 Summary
    4. Technical Appendix
  10. Chapter 5: The Normal Distribution
    1. 5.1 The Bell Shape
    2. 5.2 The Empirical Rule
    3. 5.3 Standard Normal Distribution
    4. 5.4 Normal Approximations
    5. 5.5 Summary
    6. Technical Appendix
  11. Chapter 6: Sampling Distributions
    1. 6.1 Defining a Sampling Distribution
    2. 6.2 The Importance of Sampling Distributions
    3. 6.3 An Example of a Sampling Distribution
    4. 6.4 Characteristics of a Sampling Distribution of a Mean
    5. 6.5 Sampling Distribution of a Proportion
    6. 6.6 Summary
    7. Technical Appendix
  12. Chapter 7: Confidence Intervals
    1. 7.1 Confidence Intervals for Means
    2. 7.2 Confidence Intervals for Proportions
    3. 7.3 Sample Size and the Width of Confidence Intervals
    4. 7.4 Comparing Two Proportions From the Same Poll
    5. 7.5 Summary
    6. Technical Appendix
  13. Chapter 8: Hypothesis Tests of a Population Mean
    1. 8.1 Two-Tail Hypothesis Test of a Mean
    2. 8.2 One-Tail Hypothesis Test of a Mean
    3. 8.3 -Value Approach to Hypothesis Tests
    4. 8.4 Summary
    5. Technical Appendix
  14. Chapter 9: Hypothesis Tests of Categorical Data
    1. 9.1 Two-Tail Hypothesis Test of a Proportion
    2. 9.2 One-Tail Hypothesis Test of a Proportion
    3. 9.3 Using -Values
    4. 9.4 Chi-Square Tests
    5. 9.5 Summary
    6. Technical Appendix
  15. Chapter 10: Hypothesis Tests Comparing Two Parameters
    1. 10.1 The Approach in this Chapter
    2. 10.2 Hypothesis Tests of Two Means
    3. 10.3 Hypothesis Tests of Two Variances
    4. 10.4 Hypothesis Tests of Two Proportions
    5. 10.5 Summary
    6. Technical Appendix
  16. Chapter 11: Simple Linear Regression
    1. 11.1 The Population Regression Model
    2. 11.2 A Look at the Data
    3. 11.3 Ordinary Least Squares (OLS)
    4. 11.4 The Distribution of and
    5. 11.5 Tests of Significance
    6. 11.6 Goodness of Fit
    7. 11.7 Checking for Violations of the Assumptions
    8. 11.8 Summary
    9. Technical Appendix
  17. Chapter 12: Multiple Regression
    1. 12.1 Population Regression Model
    2. 12.2 The Data
    3. 12.3 Sample Regression Function
    4. 12.4 Interpreting the Estimates
    5. 12.5 Prediction
    6. 12.6 Tests of Significance
    7. 12.7 Goodness of Fit
    8. 12.8 Multicollinearity
    9. 12.9 Summary
    10. Technical Appendix
  18. Chapter 13: More Topics in Regression
    1. 13.1 Hypothesis Tests Comparing Two Means With Regression
    2. 13.2 Hypothesis Tests Comparing More Than Two Means (ANOVA)
    3. 13.3 Interacting Variables
    4. 13.4 Nonlinearities
    5. 13.5 Time-Series Analysis
    6. 13.6 Summary
  19. Index
  20. End User License Agreement