Board Review Course - Study Materials (Study Questions, Slides and Reference Materials)-Biostatistics Study Materials

Biostatistics Study Materials

Pdf Summary

The biostatistics course outlined has three main sections with specific learning objectives for participants:<br /><br />1. <strong>Descriptive Statistics and Probability:</strong><br />   - Understand and apply methods to describe medical data through types, graphical/tabular presentations, and summary measures.<br />   - Grasp the concept of probability distribution, particularly the normal (Gaussian) distribution.<br />   - Calculate probabilities using the standard normal (Z) distribution.<br /><br />2. <strong>Inferential Statistics:</strong><br />   - Learn the reasoning behind sampling and identify various sampling methods.<br />   - Compute sampling distributions and understand the standard error of the mean.<br />   - Recognize the significance of the Central Limit Theorem.<br />   - Define and apply confidence intervals for sample size estimation.<br />   - Formulate and perform hypothesis testing procedures, including understanding errors and p-values.<br /><br />3. <strong>Applied Analysis Methods:</strong><br />   - Construct and interpret confidence intervals and hypothesis tests for comparing population means and proportions, both paired and unpaired, with known and unknown variances.<br />   - Understand and apply non-parametric tests like Median test, Mann-Whitney test, and ANOVA.<br />   - Analyze and interpret correlation results using Pearson’s and Spearman’s correlation.<br />   - Use appropriate regression methods, including simple linear, logistic, and multiple regression.<br />   - Apply survival analysis techniques such as Kaplan-Meier curves and Cox proportional hazards models.<br /><br />The course incorporates practical applications and example questions, such as evaluating statistical methods and interpreting data from research studies (like assessing the effects of night shift work on coronary heart disease risk among nurses) and selecting appropriate statistical tests for various datasets.<br /><br />The collaboration extends to meta-analysis, demonstrated by reviewing figures from published studies, determining probability from Z-scores, and making statistical decisions based on CI and hypothesis testing results. Advanced analytical techniques also include discerning between dependent and independent variables and applying regression analysis to clinical data, reflecting the detailed and practical nature of the course.<br /><br />In summary, the biostatistics course provides comprehensive coverage from descriptive to inferential statistics, equipped with practical tools to apply appropriate statistical tests, interpret results accurately, and use advanced analysis methods for real-world medical and clinical research scenarios.

Keywords

descriptive statistics

probability distribution

inferential statistics

sampling methods

confidence intervals

hypothesis testing

non-parametric tests

regression analysis

survival analysis

meta-analysis