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Statistics for Health Care Management and Administration

Author David A. Rosenthal , John F. Kros
Release Date: 2016/01/01
ISBN: 9781118712658
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Book Description

The must-have statistics guide for students of health services

Statistics for Health Care Management and Administration is a unique and invaluable resource for students of health care administration and public health. The book introduces students to statistics within the context of health care, focusing on the major data and analysis techniques used in the field. All hands-on instruction makes use of Excel, the most common spreadsheet software that is ubiquitous in the workplace. This new third edition has been completely retooled, with new content on proportions, ANOVA, linear regression, chi-squares, and more, Step-by-step instructions in the latest version of Excel and numerous annotated screen shots make examples easy to follow and understand.

Familiarity with statistical methods is essential for health services professionals and researchers, who must understand how to acquire, handle, and analyze data. This book not only helps students develop the necessary data analysis skills, but it also boosts familiarity with important software that employers will be looking for.

  • Learn the basics of statistics in the context of Excel
  • Understand how to acquire data and display it for analysis
  • Master various tests including probability, regression, and more
  • Turn test results into usable information with proper analysis

Statistics for Health Care Management and Administration gets students off to a great start by introducing statistics in the workplace context from the very beginning.

Table of Contents

  1. Title Page
  2. Copyright
  3. Dedication
  4. Preface
    1. Introducing Excel
    2. So How Did We Get to Here?
    3. Intended Level of the Textbook
    4. Textbook Organization
    5. Leading by Example(s)
  5. Acknowledgments
  6. The Authors
  7. Part 1
    1. Chapter 1: Statistics and Excel
      1. 1.1 How This Book Differs from Other Statistics Texts
      2. 1.2 Statistical Applications in Health Policy and Health Administration
      3. 1.3 What Is the “Big Picture”?
      4. 1.4 Some Initial Definitions
      5. 1.5 Five Statistical Tests
      6. Key Terms
    2. Chapter 2: Excel as a Statistical Tool
      1. 2.1 The Basics
      2. 2.2 Working and Moving Around in a Spreadsheet
      3. 2.3 Excel Functions
      4. 2.4 The =IF() Function
      5. 2.5 Excel Graphs
      6. 2.6 Sorting a String of Data
      7. 2.7 The Data Analysis Pack
      8. 2.8 Functions That Give Results in More than One Cell
      9. 2.9 The Dollar Sign ($ ) Convention for Cell References
      10. Key Terms
    3. Chapter 3: Data Acquisition: Sampling and Data Preparation
      1. 3.1 The Nature of Data
      2. 3.2 Sampling
      3. 3.3 Data Access and Preparation
      4. 3.4 Missing Data
      5. Key Terms
    4. Chapter 4: Data Display: Descriptive Presentation, Excel Graphing Capability
      1. 4.1 Creating, Displaying, and Understanding Frequency Distributions
      2. 4.2 Using the Pivot Table to Generate Frequencies of Categorical Variables
      3. 4.3 A Logical Extension of the Pivot Table: Two Variables
      4. Key Terms
    5. Chapter 5: Basic Concepts of Probability
      1. 5.1 Some Initial Concepts and Definitions
      2. 5.2 Marginal Probabilities, Joint Probabilities, and Conditional Probabilities
      3. 5.3 Binomial Probability
      4. 5.4 The Poisson Distribution
      5. 5.5 The Normal Distribution
      6. Key Terms
    6. Chapter 6: Measures of Central Tendency and Dispersion: Data Distributions
      1. 6.1 Measures of Central Tendency and Dispersion
      2. 6.2 The Distribution of Frequencies
      3. 6.3 The Sampling Distribution of the Mean
      4. 6.4 Mean and Standard Deviation of a Discrete Numerical Variable
      5. 6.5 The Distribution of a Proportion
      6. 6.6 The t Distribution
      7. Key Terms
  8. Part 2
    1. Chapter 7: Confidence Limits and Hypothesis Testing
      1. 7.1 What Is a Confidence Interval?
      2. 7.2 Calculating Confidence Limits for Multiple Samples
      3. 7.3 What Is Hypothesis Testing?
      4. 7.4 Type I and Type II Errors
      5. 7.5 Selecting Sample Sizes
      6. Key Terms
    2. Chapter 8: Statistical Tests for Categorical Data
      1. 8.1 Independence of Two Variables
      2. 8.2 Examples of Chi-Square Analyses
      3. 8.3 Small Expected Values in Cells
      4. Key Terms
    3. Chapter 9: t Tests for Related and Unrelated Data
      1. 9.1 What Is a t Test?
      2. 9.2 A t Test for Comparing Two Groups
      3. 9.3 A t Test for Related Data
      4. Key Terms
    4. Chapter 10: Analysis of Variance
      1. 10.1 One-Way Analysis of Variance
      2. 10.2 ANOVA for Repeated Measures
      3. 10.3 Factorial Analysis of Variance
      4. Key Terms
    5. Chapter 11: Simple Linear Regression
      1. 11.1 Meaning and Calculation of Linear Regression
      2. 11.2 Testing the Hypothesis of Independence
      3. 11.3 The Excel Regression Add-In
      4. 11.4 The Importance of Examining the Scatterplot
      5. 11.5 The Relationship between Regression and the t Test
      6. Key Terms
    6. Chapter 12: Multiple Regression: Concepts and Calculation
      1. 12.1 Introduction
      2. Key Terms
    7. Chapter 13: Extensions of Multiple Regression
      1. 13.1 Dummy Variables in Multiple Regression
      2. 13.2 The Best Regression Model
      3. 13.3 Correlation and Multicolinearity
      4. 13.4 Nonlinear Relationships
      5. Key Terms
    8. Chapter 14: Analysis with a Dichotomous Categorical Dependent Variable
      1. 14.1 Introduction to the Dichotomous Dependent Variable
      2. 14.2 An Example with a Dichotomous Dependent Variable: Traditional Treatments
      3. 14.3 Logit for Estimating Dichotomous Dependent Variables
      4. 14.4 A Comparison of Ordinary Least Squares, Weighted Least Squares, and Logit
      5. Key Terms
  9. Appendix A: Multiple Regression and Matrices
    1. An Introduction to Matrix Math
    2. Addition and Subtraction of Matrices
    3. Multiplication of Matrices
    4. Matrix Multiplication and Scalars
    5. Finding the Determinant of a Matrix
    6. Matrix Capabilities of Excel
    7. Explanation of Excel Output Displayed with Scientific Notation
    8. Using the b Coefficients to Generate Regression Results
    9. Calculation of All Multiple Regression Results
  10. References
  11. Glossary
    1. Index
  12. End User License Agreement
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