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Biostatistics For Dummies

Book Description

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.

Table of Contents

  1. Cover
  2. Title Page
  3. Table of Contents
  4. Introduction
  5. Part I: Beginning with Biostatistics Basics
    1. Chapter 1: Biostatistics 101
    2. Chapter 2: Overcoming Mathophobia: Reading and Understanding Mathematical Expressions
    3. Chapter 3: Getting Statistical: A Short Review of Basic Statistics
    4. Chapter 4: Counting on Statistical Software
    5. Chapter 5: Conducting Clinical Research
    6. Chapter 6: Looking at Clinical Trials and Drug Development
  6. Part II: Getting Down and Dirty with Data
    1. Chapter 7: Getting Your Data into the Computer
    2. Chapter 8: Summarizing and Graphing Your Data
    3. Chapter 9: Aiming for Accuracy and Precision
    4. Chapter 10: Having Confidence in Your Results
    5. Chapter 11: Fuzzy In Equals Fuzzy Out: Pushing Imprecision through a Formula
  7. Part III : Comparing Groups
    1. Chapter 12: Comparing Average Values between Groups
    2. Chapter 13: Comparing Proportions and Analyzing Cross-Tabulations
    3. Chapter 14: Taking a Closer Look at Fourfold Tables
    4. Chapter 15: Analyzing Incidence and Prevalence Rates in Epidemiologic Data
    5. Chapter 16 : Feeling Noninferior (Or Equivalent)
  8. Part IV: Looking for Relationships with Correlation and Regression
    1. Chapter 17: Introducing Correlation and Regression
    2. Chapter 18 : Getting Straight Talk on Straight-Line Regression
    3. Chapter 19: More of a Good Thing: Multiple Regression
    4. Chapter 20: A Yes-or-No Proposition: Logistic Regression
    5. Chapter 21: Other Useful Kinds of Regression
  9. Part V : Analyzing Survival Data
    1. Chapter 22: Summarizing and Graphing Survival Data
    2. Chapter 23: Comparing Survival Times
    3. Chapter 24: Survival Regression
  10. Part VI : The Part of Tens
    1. Chapter 25: Ten Distributions Worth Knowing
    2. Chapter 26: Ten Easy Ways to Estimate How Many Subjects You Need
  11. Cheat Sheet