Principles of biostatistics

Content: 1. Introduction2. Data Presentation Types of Numerical Data Nominal Data Ordinal Data Ranked Data Discrete Data Continuous Data Tables Frequency Distributions Relative Frequency Graphs Bar Charts Histograms Frequency Polygons One-Way Scatter Plots Box Plots Two-Way Scatter Plots Line Graphs Further Applications Review Exercises 3. Numerical Summary Measures Measures of Central Tendency Mean Median Mode Measures of Dispersion Range Interquartile Range Variance and Standard Deviation Coefficient of Variation Grouped Data Grouped Mean Grouped Variance Chebychev's Inequality Further Applications Review Exercises 4. Rates and Standardization Rates Standardization of Rates Direct Method of Standardization Indirect Method of Standardization Use of Standardized Rates Further Applications Direct Method of Standardization Indirect Method of Standardization Review Exercises 5. Life Tables Computation of the Life Table Applications of the Life Table Years of Potential Life Lost Further Applications Review Exercises 6. Probability Operations on Events and Probability Conditional Probability Bayes' Theorem Diagnostic Tests Sensitivity and Specificity Applications of Bayes' Theorem ROC Curves Calculation of Prevalence The Relative Risk and the Odds Ratio Further Applications Review Exercises 7. Theoretical Probability Distributions Probability Distributions The Binomial Distribution The Poisson Distribution The Normal Distribution Further Applications Review Exercises 8. B Sampling Distribution of the Mean B Sampling Distributions The Central Limit Theorem Applications of the Central Limit Theorem Further Applications Review Exercises 9. Confidence Intervals Two-Sided Confidence Intervals One-Sided Confidence Intervals Student's t Distribution Further Applications Review Exercises 10. Hypothesis Testing General Concepts Two-Sided Tests of Hypotheses One-Sided Tests of Hypotheses Types of Error Power Sample Size Estimation Further Applications Review Exercises 11. Comparison of Two Means Paired Samples Independent Samples Equal Variances Unequal Variances Further Applications Review Exercises 12. Analysis of Variance One-Way Analysis of Variance The Problem Sources of Variation Multiple Comparisons Procedures Further Applications Review Exercises 13. Nonparametric MethodsThe Sign Test The Wilcoxon Signed-Rank TestThe Wilcoxon Rank Sum TestAdvantages and Disadvantages ofNonparametric Methods Further Applications Review Exercises 14. Inference on Proportions Normal Approximation to the Binomial Distribution Sampling Distribution of a Proportion Confidence Intervals Hypothesis Testing Sample Size Estimation Comparison of Two Proportions Further Applications Review Exercises 15. Contingency Tables The Chi-Square Test X Tables r X c Tables McNemar's Test The Odds Ratio Berkson's Fallacy Further Applications Review Exercises 16. Multiple x Tables Simpsons Paradox The Mantei-Haenszel MethodTest of HomogeneitySummary Odds RatioTest of AssociationFurther ApplicationsReview Exercises17. Correlation The Two-Way Scatter Plot Pearson's Correlation Coefficient Spearman's Rank Correlation Coefficient Further Applications Review Exercises 18. Simple Linear Regression Regression Concepts The Model The Population Regression Line The Method of Least Squares Inference for Regression Coefficients Inference for Predicted Values Evaluation of the Model The Coefficient of Determination Residual Plots Transformations Further Applications Review Exercises 19. Multiple Regression The Model The Least-Squares Regression EquationInference for Regression CoefficientsEvaluation of the Model Indicator Variables Interaction Terms Model Selection Further Applications Review Exercises 20. Logistic Regression The Model The Logistic FunctionThe Fitted EquationMultiple Logistic RegressionIndicator Variables Further Applications Review Exercises 21. Survival Analysis The Life Table Method The Product-Limit Method The Log-Rank Test Further Applications Review Exercises 22. Sampling Theory Sampling Schemes Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Nonprobability Sampling Sources of Bias Further Applications Review Exercises