Weaver, A. and Goldberg, S. Clinical Biostatistics and Epidemiology Made Ridiculously Simple (2012).

The most important points in clinical biostatistics and epidemiology, presented intuitively with clinical examples. Valuable not only for biostatistics courses and medical Board review, but for providing a lasting clear approach to interpreting medical research reports. 104 pgs; list $22.95.
(eBook $14.99 available for
iPad)(Erratum)
Sample page: A, B, C

ISBN#9781935660026 eBook ISBN#9781935660118
 

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