Biostatistics For Dummies

Learn to: Understand key statistical concepts as they relate to biological sciences Interpret biological and statistical data in any setting Score your highest in your biostatistics course Baffled by biostatistics? Biostatisticians are charged with finding answers to some of the world's most pressing health questions: How safe or effective are drugs hitting the market today? What causes autism? What are the risk factors for cardiovascular disease? Covering the most relevant topics you'll encounter in a biostatistics course, Biostatistics For Dummies gives you plain-English explanations of important concepts and plenty of examples. Back to the basics — get up to speed on math and statistics concepts, find advice on selecting statistical software, and get an overview of clinical research The deal with data — find out how to collect data properly, summarize it concisely, display it in tables and graphs, and describe its qualities Size it up — grasp the most common statistical techniques for comparing groups: t tests, ANOVAs, chi-square tests, and Fisher Exact tests Let's regress — learn how to test for and quantify the relationship between two or more variables, from a simple straight-line regression to multiple, logistic, nonlinear, and other kinds of regression Survive and thrive — see how to calculate survival curves, test for a difference in survival between two or more groups of subjects, and apply the methods of regression analysis to survival data Open the book and find: Basic math and statistical formulas, concepts, and techniques you need to know The big picture of clinical research How to summarize and graph data The scoop on accuracy, precision, standard errors, and confidence intervals Ways to compare groups Common distribution functions Simple rules for sample-size calculations

Introduction 1 Part I: Beginning with Biostatistics Basics 7 Chapter 1: Biostatistics 101 9 Chapter 2: Overcoming Mathophobia: Reading and Understanding Mathematical Expressions 17 Chapter 3: Getting Statistical: A Short Review of Basic Statistics 31 Chapter 4: Counting on Statistical Software 51 Chapter 5: Conducting Clinical Research 61 Chapter 6: Looking at Clinical Trials and Drug Development 77 Part II: Getting Down and Dirty with Data 91 Chapter 7: Getting Your Data into the Computer 93 Chapter 8: Summarizing and Graphing Your Data 103 Chapter 9: Aiming for Accuracy and Precision 121 Chapter 10: Having Confi dence in Your Results 133 Chapter 11: Fuzzy In Equals Fuzzy Out: Pushing Imprecision through a Formula 143 Part III: Comparing Groups 153 Chapter 12: Comparing Average Values between Groups 155 Chapter 13: Comparing Proportions and Analyzing Cross–Tabulations 173 Chapter 14: Taking a Closer Look at Fourfold Tables 189 Chapter 15: Analyzing Incidence and Prevalence Rates in Epidemiologic Data 203 Chapter 16: Feeling Noninferior (Or Equivalent) 211 Part IV: Looking for Relationships with Correlation and Regression 219 Chapter 17: Introducing Correlation and Regression 221 Chapter 18: Getting Straight Talk on Straight–Line Regression 233 Chapter 19: More of a Good Thing: Multiple Regression 251 Chapter 20: A Yes–or–No Proposition: Logistic Regression 267 Chapter 21: Other Useful Kinds of Regression 291 Part V: Analyzing Survival Data 311 Chapter 22: Summarizing and Graphing Survival Data 313 Chapter 23: Comparing Survival Times 331 Chapter 24: Survival Regression 339 Part VI: The Part of Tens 357 Chapter 25: Ten Distributions Worth Knowing 359 Chapter 26: Ten Easy Ways to Estimate How Many Subjects You Need 369 Index 375

John C. Pezzullo , PhD, has held faculty appointments in the departments of biomathematics and biostatistics, pharmacology, nursing, and internal medicine at Georgetown University. He is semi–retired and continues to teach biostatistics and clinical trial design online to Georgetown University students.