What is included with this book?
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.
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.
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