Statistics for Health Care Management and Administration: Working with Excel

An Up–To–Date, Essential Resource for Understanding and Applying Statistical Analysis Techniques in Health Care

Thoroughly revised and updated, the third edition of Statistics for Health Care Management and Administration offers an invaluable resource for students of health care administration and public health. The book shows how to apply quantitative methods in health administration, health policy, public health, health information management, and nursing. The authors focus on the major data and analysis techniques that make use of Excel, the spreadsheet software that is most commonly used in the health care workplace.

The third edition contains new content on proportions, ANOVA, linear regression, chi–squares, and much more. The authors offer step–by–step instructions in the latest version of Excel and include numerous annotated screenshots that make examples easy to follow and comprehend.

Statistics for Health Care Management and Administration gives students the information and tools they need to:

Acquire and comprehend the basics of statistics using the power of Excel Master various tests including probability, regression, and many more Transform test results into practical information that is grounded in sound analysis Understand the implications of unfolding legislation and other developments such as payment for quality and penalties for readmissions

Statistics for Health Care Management and Administration introduces health care students to statistical analysis as it is applied in a workplace context.

Preface

Introducing Excel

So How Did We Get to Here?

Intended Level of the Textbook

Textbook Organization

Leading by Example(s)

Acknowledgments

About the Authors

Part 1

Chapter 1: Statistics and Excel

1.1 How This Book Differs from Other Statistics Texts

1.2 Statistical Applications in Health Policy and Health Administration

Exercises for Section 1.2

1.3 What Is the Big Picture ?

1.4 Some Initial Definitions

Exercises for Section 1.4

1.5 Five Statistical Tests

Exercises for Section 1.5

Key Terms

Chapter 2: Excel as a Statistical Tool

2.1 The Basics

Exercises for Section 2.1

2.2 Working and Moving Around in a Spreadsheet

Exercises for Section 2.2

2.3 Excel Functions

Exercises for Section 2.3

2.4 The =IF() Function

Exercises for Section 2.4

2.5 Excel Graphs

Exercises for Section 2.5

2.6 Sorting a String of Data

Exercise for Section 2.6

2.7 The Data Analysis Pack

2.8 Functions That Give Results in More Than One Cell

Exercises for Section 2.8

2.9 The Dollar Sign ($) Convention for Cell References

Key Terms

Chapter 3: Data Acquisition: Sampling and Data Preparation

3.1 The Nature of Data

Exercises for Section 3.1

3.2 Sampling

Exercises for Section 3.2

3.3 Data Access and Preparation

Exercises for Section 3.3

3.4 Missing Data

Key Terms

Chapter 4: Data Display: Descriptive Presentation, Excel Graphing Capability

4.1 Creating, Displaying, and Understanding Frequency Distributions

Exercises for Section 4.1

4.2 Using the Pivot Table to Generate Frequencies of Categorical Variables

Exercises for Section 4.2

4.3 A Logical Extension of the Pivot Table: Two Variables

Exercises for Section 4.3

Key Terms

Chapter 5: Basic Concepts of Probability

5.1 Some Initial Concepts and Definitions

Exercises for Section 5.1

5.2 Marginal Probabilities, Joint Probabilities, and Conditional Probabilities

Exercises for Section 5.2

5.3 Binomial Probability

Exercises for Section 5.3

5.4 The Poisson Distribution

Exercises for Section 5.4

5.5 The Normal Distribution

Key Terms

Chapter 6: Measures of Central Tendency and Dispersion: Data Distributions

6.1 Measures of Central Tendency and Dispersion

Exercises for Section 6.1

6.2 The Distribution of Frequencies

Exercises for Section 6.2

6.3 The Sampling Distribution of the Mean

Exercises for Section 6.3

6.4 Mean and Standard Deviation of a Discrete Numerical Variable

Exercises for Section 6.4

6.5 The Distribution of a Proportion

Exercises for Section 6.5

6.6 The t Distribution

Exercises for Section 6.6

Key Terms

Part 2

Chapter 7: Confidence Limits and Hypothesis Testing

7.1 What Is a Confidence Interval?

Exercises for Section 7.1

7.2 Calculating Confidence Limits for Multiple Samples

Exercises for Section 7.2

7.3 What Is Hypothesis Testing?

Exercises for Section 7.3

7.4 Type I and Type II Errors

Exercises for Section 7.4

7.5 Selecting Sample Sizes

Exercises for Section 7.5

Key Terms

Chapter 8: Statistical Tests for Categorical Data

8.1 Independence of Two Variables

Exercises for Section 8.1

8.2 Examples of Chi–Square Analyses

Exercises for Section 8.2

8.3 Small Expected Values in Cells

Exercises for Section 8.3

Key Terms

Chapter 9: t Tests for Related and Unrelated Data

9.1 What Is a t Test?

Exercises for Section 9.1

9.2 A t Test for Comparing Two Groups

Exercises for Section 9.2

9.3 A t Test for Related Data

Exercises for Section 9.3

Key Terms

Chapter 10: Analysis of Variance

10.1 One–Way Analysis of Variance

Exercises for Section 10.1

10.2 ANOVA for Repeated Measures

Exercises for Section 10.2

10.3 Factorial Analysis of Variance

Exercises for Section 10.3

Key Terms

Chapter 11:Simple Linear Regression

11.1 Meaning and Calculation of Linear Regression

Exercises for Section 11.1

11.2 Testing the Hypothesis of Independence

Exercises for Section 11.2

11.3 The Excel Regression Add–In

Exercises for Section 11.3

11.4 The Importance of Examining the Scatterplot

11.5 The Relationship Between Regression and the t Test

Exercises for Section 11.5

Key Terms

Chapter 12: Multiple Regression: Concepts and Calculation

12.1 Introduction

Exercises for Section 12.1

Key Terms

Chapter 13: Extensions of Multiple Regression

13.1 Dummy Variables in Multiple Regression

Exercises for Section 13.1

13.2 The Best Regression Model

Exercises for Section 13.2

13.3 Correlation and Multi–colinearity

Exercises for Section 13.3

13.4 Nonlinear Relationships

Exercises for Section 13.4

Key Terms

Chapter 14: Analysis with a Dichotomous Categorical Dependent Variable

14.1 Introduction to the Dichotomous Dependent Variable

14.2 An Example with a Dichotomous Dependent Variable: Traditional Treatments

Exercises for Section 14.2

14.3 Logit for Estimating Dichotomous Dependent Variables

Exercises for Section 14.3

14.4 A Comparison of Ordinary Least Squares, Weighted Least Squares, and Logit

Exercises for Section 14.4

Key Terms

Appendix A: Multiple Regression and Matrices

An Introduction to Matrix Math

Addition and Subtraction of Matrices

Multiplication of Matrices

Matrix Multiplication and Scalars

Finding the Determinant of a Matrix

Matrix Capabilities of Excel

Explanation of Excel Output Displayed with Scientific Notation

Using the b Coefficients to Generate Regression Results

Calculation of All Multiple Regression Results

Exercises for Appendix A

References

Index

JOHN F. KROS, PHD, is the Vincent K. McMahon Distinguished Professor of Business in the Marketing and Supply Chain Management Department in the College of Business at East Carolina University.

DAVID A. ROSENTHAL, PHD, is Professor and Chair of Health Care Management at Baptist Memorial College of Health Sciences.