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

<p><b>John C. Pezzullo</b>, 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.</p>

<p>Learn to:</p> <ul> <li>Understand key statistical concepts as they relate to biological sciences</li> <li>Interpret biological and statistical data in any setting</li> <li>Score your highest in your biostatistics course</li> </ul> <p>Baffled by biostatistics?</p> <p>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, <i>Biostatistics For Dummies</i> gives you plain-English explanations of important concepts and plenty of examples.</p> <ul> <li>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</li> <li>The deal with data — find out how to collect data properly, summarize it concisely, display it in tables and graphs, and describe its qualities</li> <li>Size it up — grasp the most common statistical techniques for comparing groups: t tests, ANOVAs, chi-square tests, and Fisher Exact tests</li> <li>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</li> <li>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</li> </ul> <p>Open the book and find:</p> <ul> <li>Basic math and statistical formulas, concepts, and techniques you need to know</li> <li>The big picture of clinical research</li> <li>How to summarize and graph data</li> <li>The scoop on accuracy, precision, standard errors, and confidence intervals</li> <li>Ways to compare groups</li> <li>Common distribution functions</li> <li>Simple rules for sample-size calculations</li> </ul>

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