Clinical Biostatistics and Epidemiology Made Ridiculously Simple
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Clinical Biostatistics and Epidemiology Made Ridiculously Simple

by Ann Weaver, Stephen Goldberg,

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The most important points in clinical biostatistics, presented intuitively with clinical examples. Because intuitive concepts are the easiest to learn and retain, this book minimizes math and emphasizes concepts. From terminology to research design to various statistical testing, this text provides a lasting clear approach to interpreting medical research reports. Valuable for biostatistics courses.

Excellent USMLE Board Review.

  • Pages: 104
  • Publication: Edition 1 (April 1, 2012)
  • Language: English
  • ISBN: 9781935660026

About the Authors

Ann Weaver

Ann Weaver, PhD, Professor, Statistics and Research, Program Chair of Research and Statistics, Argosy University, Sarasota FL.

Stephen Goldberg

Stephen Goldberg, MD, a graduate of the Albert Einstein College of Medicine, trained in Neurology, Ophthalmology, and Family Medicine. He is a neurologic researcher, teacher, computer programmer, writer, editor, and president of the Medmaster publishing company. Dr. Goldberg has published numerous papers on neuronal development and regeneration through research done at the Albert Einstein College of Medicine, National Institutes of Health, New York Medical College and the University of Miami. He is the author of the best-selling book, Clinical Neuroanatomy Made Ridiculously Simple, as well as the interactive computer program Neurologic Localization. As a coordinator of neuroanatomy education at the University of Miami Miller School of Medicine for 25 years, his reputation is that of an educator who can simplify complex topics. He received the George Paff Most Outstanding Professor Teaching Award 11 times at the U of M and was invited to be the keynote speaker at the medical school graduation commencement at the Washington University School of Medicine in St. Louis in 2004. He has also authored textbooks of Anatomy, Physiology, Biochemistry, Biostatistics, Neurology, Ophthalmology and Computer Programming, as well as many interactive computer programs on a variety of medical topics. His diverse background has bolstered his life-long interest in the Mind/ Body problem, for which he has published five previous books. Consciousness Made Ridiculously Simple is a distillation and advancement of his past books, in which he aims to resolve the mystery of the nature and origin of consciousness.

The most important points in clinical biostatistics, presented intuitively with clinical examples. Because intuitive concepts are the easiest to learn and retain, this book minimizes math and emphasizes concepts. From terminology to research design to various statistical testing, this text provides a lasting clear approach to interpreting medical research reports. Valuable for biostatistics courses.

Excellent USMLE Board Review.

  • Pages: 104
  • Publication: Edition 1 (April 1, 2012)
  • Language: English

About the Authors

Ann Weaver

Ann Weaver, PhD, Professor, Statistics and Research, Program Chair of Research and Statistics, Argosy University, Sarasota FL.

Stephen Goldberg

Stephen Goldberg, MD, a graduate of the Albert Einstein College of Medicine, trained in Neurology, Ophthalmology, and Family Medicine. He is a neurologic researcher, teacher, computer programmer, writer, editor, and president of the Medmaster publishing company. Dr. Goldberg has published numerous papers on neuronal development and regeneration through research done at the Albert Einstein College of Medicine, National Institutes of Health, New York Medical College and the University of Miami. He is the author of the best-selling book, Clinical Neuroanatomy Made Ridiculously Simple, as well as the interactive computer program Neurologic Localization. As a coordinator of neuroanatomy education at the University of Miami Miller School of Medicine for 25 years, his reputation is that of an educator who can simplify complex topics. He received the George Paff Most Outstanding Professor Teaching Award 11 times at the U of M and was invited to be the keynote speaker at the medical school graduation commencement at the Washington University School of Medicine in St. Louis in 2004. He has also authored textbooks of Anatomy, Physiology, Biochemistry, Biostatistics, Neurology, Ophthalmology and Computer Programming, as well as many interactive computer programs on a variety of medical topics. His diverse background has bolstered his life-long interest in the Mind/ Body problem, for which he has published five previous books. Consciousness Made Ridiculously Simple is a distillation and advancement of his past books, in which he aims to resolve the mystery of the nature and origin of consciousness.

Table of Contents

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  • TABLE OF CONTENTS

    PART I. INTRODUCTION

    CHAPTER 1. TERMINOLOGY Population, Sample, and Element Descriptive vs. Inferential Statistics Parameter vs. Statistic Sampling Error vs. Selection Bias Imprecision vs. Bias (Inaccuracy) Validity vs. Reliability Independent vs. Dependent Variables Normal (Gaussian), Skewed and Kurtotic curves Multiplication and Addition Rules of Probability Statistical Significance vs. Clinical Significance Statistical Abnormality vs. Clinical Abnormality

    CHAPTER 2. MEAN, MEDIAN, AND MODE Mean Median Mode What’s Wrong Here? *#!!

    CHAPTER 3. RANGE, VARIATION, AND STANDARD DEVIATION Range Variance Standard Deviation Coefficient of Variation

    CHAPTER 4. KINDS OF DATA Nominal Data Ordinal Data Interval Data Ratio Data

    PART II. RESEARCH DESIGN

    CHAPTER 5. KINDS OF STUDIES Randomized Control Studies Matching Studies Stratified Randomization Studies Blind Studies Prospective (Cohort; Longitudinal) Studies Retrospective (Case-control) Studies Cross-sectional (Prevalence) Studies Experimental vs. Observational Studies Case Series and Case Reports Meta-analysis Crossover, Between-subjects, and Within-subjects Studies Therapeutic Trials

    CHAPTER 6. GRAPHING Bar Graphs (Bar Charts) Tables Histograms Line Graphs Cumulative Frequency Curves Box-and-Whiskers Plots Stem-and-Leaf Plots Scattergrams Survival Curves

    CHAPTER 7. HYPOTHESIS TESTING The Null and Alternative Hypotheses Rejecting the Null Hypothesis

    PART III. STATISTICAL TESTS

    Parametric vs. Nonparametric Tests

    CHAPTER 8. DESCRIPTIVE STATISTICS The Z-score

    CHAPTER 9. INFERENTIAL STATISTICS Confidence Intervals vs. Hypothesis Testing and P-values

    CHAPTER 10. STANDARD ERROR OF THE MEAN The Central Limit Theorem Standard Error of the Mean (SEM)

    CHAPTER 11. THE T-TEST The Meaning of the T-Test Comparing Two Samples

    CHAPTER 12. ONE-TAILED VS. TWO-TAILED STUDIES

    CHAPTER 13. P-ING (PEE-ING) ALL OVER THE PLACE

    CHAPTER 14. TYPE I AND TYPE II ERRORS AND POWER Type I and Type II Errors Power Effect Size Bayesian Thinking Calculation of Sample Size

    CHAPTER 15. ANOVA (ANALYSIS OF VARIANCE) ANOVA and F-ratio MANOVA and ANCOVA

    CHAPTER 16. CORRELATION AND REGRESSION Correlation Techniques Correlation Coefficient Coefficient of Determination Correlation Does Not Mean Causation Criteria of Causality Regression Kinds of Regression Analysis Regression to the Mean

    CHAPTER 17. NONPARAMETRIC TESTS Chi Square Goodness-of-Fit Test Nonparametric Tests That Use Ranking Nonparametric Tests That Do Not Use Ranking

    CHAPTER 18. EPIDEMIOLOGICAL TESTS Incidence vs. Prevalence Mortality, Morbidity, and Case Fatality Absolute Risk vs. Relative Risk (RR) Odds and Odds Ratio (Relative Odds) Absolute Risk Reduction (Attributable Risk) vs. Relative Risk Reduction Number Needed to Treat (NNT) Number Needed to Harm (NNH) Sensitivity vs. Specificity Positive and Negative Predictive Values

    PART IV. ARE THE RESEARCH CONCLUSIONS CORRECT?

    CHAPTER 19. WHAT'S WRONG HERE? *#!! Who Says So? How Does the Researcher Know? What's Missing? Did Someone Change the Subject? Does It Make Sense?

    Appendix A. The Z table Appendix B. The T table Appendix C. The Chi-square Table References INDEX

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