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,…mehr
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
Preface xiii Introducing Excel xiii So How Did We Get to Here? xiii Intended Level of the Textbook xiv Textbook Organization xiv Leading by Example(s) xv Acknowledgments xvii The Authors xix Part 1 1 Chapter 1 Statistics and Excel 3 1.1 How This Book Differs from Other Statistics Texts 3 1.2 Statistical Applications in Health Policy and Health Administration 4 Exercises for Section 1.2 14 1.3 What Is the ''Big Picture''? 15 1.4 Some Initial Definitions 16 Exercises for Section 1.4 26 1.5 Five Statistical Tests 28 Exercises for Section 1.5 30 Chapter 2 Excel as a Statistical Tool 33 2.1 The Basics 33 Exercises for Section 2.1 35 2.2 Working and Moving Around in a Spreadsheet 36 Exercises for Section 2.2 41 2.3 Excel Functions 41 Exercises for Section 2.3 46 2.4 The =IF() Function 47 Exercises for Section 2.4 50 2.5 Excel Graphs 51 Exercises for Section 2.5 56 2.6 Sorting a String of Data 57 Exercise for Section 2.6 60 2.7 The Data Analysis Pack 61 2.8 Functions That Give Results in More than One Cell 63 Exercises for Section 2.8 66 2.9 The Dollar Sign ($) Convention for Cell References 67 Chapter 3 Data Acquisition: Sampling and Data Preparation 71 3.1 The Nature of Data 71 Exercises for Section 3.1 78 3.2 Sampling 79 Exercises for Section 3.2 93 3.3 Data Access and Preparation 94 Exercises for Section 3.3 107 3.4 Missing Data 108 Chapter 4 Data Display: Descriptive Presentation, Excel Graphing Capability 111 4.1 Creating, Displaying, and Understanding Frequency Distributions 111 Exercises for Section 4.1 129 4.2 Using the Pivot Table to Generate Frequencies of Categorical Variables131 Exercises for Section 4.2 135 4.3 A Logical Extension of the Pivot Table: Two Variables 135 Exercises for Section 4.3 140 Chapter 5 Basic Concepts of Probability 141 5.1 Some Initial Concepts and Definitions 141 Exercises for Section 5.1 150 5.2 Marginal Probabilities, Joint Probabilities, and Conditional Probabilities 150 Exercises for Section 5.2 160 5.3 Binomial Probability 161 Exercises for Section 5.3 171 5.4 The Poisson Distribution 173 Exercises for Section 5.4 178 5.5 The Normal Distribution 178 Chapter 6 Measures of Central Tendency and Dispersion: Data Distributions 183 6.1 Measures of Central Tendency and Dispersion 183 Exercises for Section 6.1 196 6.2 The Distribution of Frequencies 197 Exercises for Section 6.2 208 6.3 The Sampling Distribution of the Mean 209 Exercises for Section 6.3 219 6.4 Mean and Standard Deviation of a Discrete Numerical Variable 220 Exercises for Section 6.4 222 6.5 The Distribution of a Proportion 222 Exercises for Section 6.5 227 6.6 The t Distribution 227 Exercises for Section 6.6 232 Part 2 235 Chapter 7 Confidence Limits and Hypothesis Testing 237 7.1 What Is a Confidence Interval? 237 Exercises for Section 7.1 243 7.2 Calculating Confidence Limits for Multiple Samples 244 Exercises for Section 7.2 246 7.3 What Is Hypothesis Testing? 247 Exercises for Section 7.3 249 7.4 Type I and Type II Errors 250 Exercises for Section 7.4 266 7.5 Selecting Sample Sizes 267 Exercises for Section 7.5 269 Chapter 8 Statistical Tests for Categorical Data 271 8.1 Independence of Two Variables 271 Exercises for Section 8.1 282 8.2 Examples of Chi-Square Analyses283 Exercises for Section 8.2 289 8.3 Small Expected Values in Cells 290 Exercises for Section 8.3 292 Chapter 9 t Tests for Related and Unrelated Data 295 9.1 What Is a t Test? 295 Exercises for Section 9.1 302 9.2 A t Test for Comparing Two Groups 303 Exercises for Section 9.2 316 9.3 A t Test for Related Data 318 Exercises for Section 9.3 321 Chapter 10 Analysis of Variance 323 10.1 One-Way Analysis of Variance 323 Exercises for Section 10.1 339 10.2 ANOVA for Repeated Measures 340 Exercises for Section 10.2 348 10.3 Factorial Analysis of Variance 349 Exercises for Section 10.3 362 Chapter 11 Simple Linear Regression 365 11.1 Meaning and Calculation of Linear Regression 365 Exercises for Section 11.1 373 11.2 Testing the Hypothesis of Independence 374 Exercises for Section 11.2 380 11.3 The Excel Regression Add-In 381 Exercises for Section 11.3 388 11.4 The Importance of Examining the Scatterplot 388 11.5 The Relationship between Regression and the t Test 391 Exercises for Section 11.5 392 Chapter 12 Multiple Regression: Concepts and Calculation 395 12.1 Introduction 395 Exercises for Section 12.1 406 Chapter 13 Extensions ofMultiple Regression 409 13.1 Dummy Variables in Multiple Regression 409 Exercises for Section 13.1 420 13.2 The Best Regression Model 421 Exercises for Section 13.2 431 13.3 Correlation and Multicolinearity 432 Exercises for Section 13.3 435 13.4 Nonlinear Relationships 435 Exercises for Section 13.4 447 Chapter 14 Analysis with a Dichotomous Categorical Dependent Variable 449 14.1 Introduction to the Dichotomous Dependent Variable 450 14.2 An Example with a Dichotomous Dependent Variable: Traditional Treatments 451 Exercises for Section 14.2 462 14.3 Logit for Estimating Dichotomous Dependent Variables 463 Exercises for Section 14.3 475 14.4 A Comparison of Ordinary Least Squares, Weighted Least Squares, and Logit 476 Exercises for Section 14.4 480 Appendix A Multiple Regression and Matrices 481 An Introduction to Matrix Math 481 Addition and Subtraction of Matrices 482 Multiplication of Matrices 483 Matrix Multiplication and Scalars 484 Finding the Determinant of a Matrix 484 Matrix Capabilities of Excel 486 Explanation of Excel Output Displayed with Scientific Notation 489 Using the b Coefficients to Generate Regression Results 490 Calculation of All Multiple Regression Results 491 Exercises for Appendix A 494 References 497 Glossary 499 Index 513
Preface xiii Introducing Excel xiii So How Did We Get to Here? xiii Intended Level of the Textbook xiv Textbook Organization xiv Leading by Example(s) xv Acknowledgments xvii The Authors xix Part 1 1 Chapter 1 Statistics and Excel 3 1.1 How This Book Differs from Other Statistics Texts 3 1.2 Statistical Applications in Health Policy and Health Administration 4 Exercises for Section 1.2 14 1.3 What Is the ''Big Picture''? 15 1.4 Some Initial Definitions 16 Exercises for Section 1.4 26 1.5 Five Statistical Tests 28 Exercises for Section 1.5 30 Chapter 2 Excel as a Statistical Tool 33 2.1 The Basics 33 Exercises for Section 2.1 35 2.2 Working and Moving Around in a Spreadsheet 36 Exercises for Section 2.2 41 2.3 Excel Functions 41 Exercises for Section 2.3 46 2.4 The =IF() Function 47 Exercises for Section 2.4 50 2.5 Excel Graphs 51 Exercises for Section 2.5 56 2.6 Sorting a String of Data 57 Exercise for Section 2.6 60 2.7 The Data Analysis Pack 61 2.8 Functions That Give Results in More than One Cell 63 Exercises for Section 2.8 66 2.9 The Dollar Sign ($) Convention for Cell References 67 Chapter 3 Data Acquisition: Sampling and Data Preparation 71 3.1 The Nature of Data 71 Exercises for Section 3.1 78 3.2 Sampling 79 Exercises for Section 3.2 93 3.3 Data Access and Preparation 94 Exercises for Section 3.3 107 3.4 Missing Data 108 Chapter 4 Data Display: Descriptive Presentation, Excel Graphing Capability 111 4.1 Creating, Displaying, and Understanding Frequency Distributions 111 Exercises for Section 4.1 129 4.2 Using the Pivot Table to Generate Frequencies of Categorical Variables131 Exercises for Section 4.2 135 4.3 A Logical Extension of the Pivot Table: Two Variables 135 Exercises for Section 4.3 140 Chapter 5 Basic Concepts of Probability 141 5.1 Some Initial Concepts and Definitions 141 Exercises for Section 5.1 150 5.2 Marginal Probabilities, Joint Probabilities, and Conditional Probabilities 150 Exercises for Section 5.2 160 5.3 Binomial Probability 161 Exercises for Section 5.3 171 5.4 The Poisson Distribution 173 Exercises for Section 5.4 178 5.5 The Normal Distribution 178 Chapter 6 Measures of Central Tendency and Dispersion: Data Distributions 183 6.1 Measures of Central Tendency and Dispersion 183 Exercises for Section 6.1 196 6.2 The Distribution of Frequencies 197 Exercises for Section 6.2 208 6.3 The Sampling Distribution of the Mean 209 Exercises for Section 6.3 219 6.4 Mean and Standard Deviation of a Discrete Numerical Variable 220 Exercises for Section 6.4 222 6.5 The Distribution of a Proportion 222 Exercises for Section 6.5 227 6.6 The t Distribution 227 Exercises for Section 6.6 232 Part 2 235 Chapter 7 Confidence Limits and Hypothesis Testing 237 7.1 What Is a Confidence Interval? 237 Exercises for Section 7.1 243 7.2 Calculating Confidence Limits for Multiple Samples 244 Exercises for Section 7.2 246 7.3 What Is Hypothesis Testing? 247 Exercises for Section 7.3 249 7.4 Type I and Type II Errors 250 Exercises for Section 7.4 266 7.5 Selecting Sample Sizes 267 Exercises for Section 7.5 269 Chapter 8 Statistical Tests for Categorical Data 271 8.1 Independence of Two Variables 271 Exercises for Section 8.1 282 8.2 Examples of Chi-Square Analyses283 Exercises for Section 8.2 289 8.3 Small Expected Values in Cells 290 Exercises for Section 8.3 292 Chapter 9 t Tests for Related and Unrelated Data 295 9.1 What Is a t Test? 295 Exercises for Section 9.1 302 9.2 A t Test for Comparing Two Groups 303 Exercises for Section 9.2 316 9.3 A t Test for Related Data 318 Exercises for Section 9.3 321 Chapter 10 Analysis of Variance 323 10.1 One-Way Analysis of Variance 323 Exercises for Section 10.1 339 10.2 ANOVA for Repeated Measures 340 Exercises for Section 10.2 348 10.3 Factorial Analysis of Variance 349 Exercises for Section 10.3 362 Chapter 11 Simple Linear Regression 365 11.1 Meaning and Calculation of Linear Regression 365 Exercises for Section 11.1 373 11.2 Testing the Hypothesis of Independence 374 Exercises for Section 11.2 380 11.3 The Excel Regression Add-In 381 Exercises for Section 11.3 388 11.4 The Importance of Examining the Scatterplot 388 11.5 The Relationship between Regression and the t Test 391 Exercises for Section 11.5 392 Chapter 12 Multiple Regression: Concepts and Calculation 395 12.1 Introduction 395 Exercises for Section 12.1 406 Chapter 13 Extensions ofMultiple Regression 409 13.1 Dummy Variables in Multiple Regression 409 Exercises for Section 13.1 420 13.2 The Best Regression Model 421 Exercises for Section 13.2 431 13.3 Correlation and Multicolinearity 432 Exercises for Section 13.3 435 13.4 Nonlinear Relationships 435 Exercises for Section 13.4 447 Chapter 14 Analysis with a Dichotomous Categorical Dependent Variable 449 14.1 Introduction to the Dichotomous Dependent Variable 450 14.2 An Example with a Dichotomous Dependent Variable: Traditional Treatments 451 Exercises for Section 14.2 462 14.3 Logit for Estimating Dichotomous Dependent Variables 463 Exercises for Section 14.3 475 14.4 A Comparison of Ordinary Least Squares, Weighted Least Squares, and Logit 476 Exercises for Section 14.4 480 Appendix A Multiple Regression and Matrices 481 An Introduction to Matrix Math 481 Addition and Subtraction of Matrices 482 Multiplication of Matrices 483 Matrix Multiplication and Scalars 484 Finding the Determinant of a Matrix 484 Matrix Capabilities of Excel 486 Explanation of Excel Output Displayed with Scientific Notation 489 Using the b Coefficients to Generate Regression Results 490 Calculation of All Multiple Regression Results 491 Exercises for Appendix A 494 References 497 Glossary 499 Index 513
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