Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health. In years past this course has been mainly a graduate-level requirement; however its application is growing and course offerings at the undergraduate level are exploding. Biostatistics For Dummies is an excellent resource for those taking a course, as well as for those in need of a handy reference to this complex material. Biostatisticians analysts of biological data 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? Are those risk factors different for men and women or different ethnic groups? Biostatistics For Dummies examines these and other questions associated with the study of biostatistics.
* Provides plain-English explanations of techniques and clinical examples to help * Serves as an excellent course supplement for those struggling with the complexities of the biostatistics * Tracks to a typical, introductory biostatistics course Biostatistics For Dummies is an excellent resource for anyone looking to succeed in this difficult course.
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.
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 Confidence 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