Details

Statistics for Health Care Management and Administration

Working with Excel
Public Health/Epidemiology and Biostatistics 4. Aufl.

von: David A. Rosenthal, John F. Kros
76,99 €
Verlag:	Wiley
Format:	EPUB
Veröffentl.:	17.07.2023
ISBN/EAN:	9781119901686
Sprache:	englisch
Anzahl Seiten:	560

In den Warenkorb

Als Gutschein

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

Titelbeschreibung

The must-have statistics guide for students of health services Statistics for Health Care Management and Administration: Working with Excel introduces the uses of statistics in healthcare management and administration using the features and functions of Microsoft Excel. The book introduces students to statistics within the context of health care, focusing on the major data and analysis techniques used in the field. Step-by-step instructions in the latest version of Excel and numerous annotated screen shots make examples easy to follow and understand. This updated fourth edition provides the same content and explanations that have made the previous editions so popular, offering revisions drawn directly from universities where the book has been used. All content has been brought current with the newest version of excel, and changes in the field of healthcare administration are covered as well. Statistics for Health Care Management and Administration gets students off to a great start by introducing statistics in the context of their chosen field. <ul> <li>Learn the basics of statistics in the context of Excel</li> <li>Understand how to acquire data and display it for analysis</li> <li>Master important concepts and tests, including regression</li> <li>Turn test results into usable information with proper analysis</li></ul>This book not only helps students develop the necessary data analysis skills, but also boosts familiarity with important software that employers will be looking for.

Inhaltsverzeichnis

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 About the Companion Website xxi 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 Variables 131 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 Analyses 283 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 of Multiple 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

Autorenportrait

David A. Rosenthal is a Chief Information Officer at CampusWorks, Inc. He has over 20 years of health care industry experience in both academic and practitioner settings, having served in roles specific to hospital information technology leadership, multispecialty practice administration, and ambulatory services project management. Rosenthal earned a Master of Public Administration degree from Valdosta State University, and a PhD in Technology Management from Indiana State University. David is a proud veteran of the U.S. Air Force, and resides in Oakland, Tennessee with his wife Allyson. John F. Kros is the Vincent K. McMahon Distinguished Professor in the Marketing and Supply Chain Management Department in the College of Business at East Carolina University, in Greenville, North Carolina. He teaches business decision modeling, statistics, operations and supply chain management, and purchasing and materials management courses. Kros was honored as the College of Business’s Scholar/Teacher for 2004???2005, again in 2009???2010, was awarded the College of Business Commerce Club’s highest honor, the Teaching Excellence Award, for 2006 and again in 2011, in 2013???2014 was awarded the East Carolina Alumni Association Outstanding Teaching Award, and in 2014???2015 was awarded the Board of Governors Distinguished Professor for Teaching Award. Kros earned his PhD in systems engineering from the University of Virginia, his MBA from Santa Clara University, and his BBA from the University of Texas at Austin. His research interests include health care operations, applied statistics, design of experiments, multi-objective decision making, Taguchi methods, and applied decision analysis. His textbook titled Spreadsheet Modeling for Business Decisions is in the fifth edition. He is also coauthor of Health Care Operations and Supply Chain Management.

Back cover copy

An up-to-date, essential resource for understanding and applying statistical analysis techniques in the health care workplace Statistics for Health Care Management and Administration is an invaluable resource for students of health care administration and public health. The book shows how to apply key quantitative methods using the features and functions of Microsoft Excel. Learners will follow clear instructions and annotated screenshots to work through the major data analysis techniques used in health care related fields. This fourth edition represents an important update of all content to conform to the latest release of Excel. Additionally, the homework problems have been revised and the text has been streamlined to emphasize the most essential topics for today’s students. Statistics for Health Care Management and Administration enables students to: <ul><li>Harness the power of Excel to learn basic statistics in a hands-on way</li> <li>Master probability, regression analysis, statistical significance, and many more</li> <li>Transform sound statistical analysis into practical information</li> <li>Utilize health care???specific data and examples to enhance job readiness</li></ul> Statistics for Health Care Management and Administration introduces statistical analysis to students in health administration, health policy, public health, health information management, nursing, and beyond.