Course Summary

Day 1: Introductory Biostatistics

Module 1

Measurement scale/types of data, sample selection; randomized clinical trial (RCT), case-control study, cross-sectional study, cohort study, matched case control study

Module 2

Summarization of data using some simple statistical methods (e.g., mean, median, quartiles, sd, etc) and graphical presentation of data (e.g., box-plot, bar-diagram, phi-chart, histogram, scatter plot, etc.)

Module 3

Quantifying uncertainty in data analysis

Module 4

Comparing two methods (e.g., placebo vs treatment; new treatment vs standard treatment ) or comparing two groups of patients – 95% Confidence Interval.

Module 5

Comparing two methods or two groups of patients using p-value (how strong the evidence that the two methods are the same/different?) – Hypothesis Test.

Module 6

Comparing more than two groups – Analysis of Variance (ANOVA)

Day 2: Advanced Biostatistics

Module 7

Evaluating the association between outcome and exposure – e.g., assessing the association between development of overian cancer and use of oral contraceptive – Chi-square Test

Module 8

Risk comparison or measuring the risk, e.g, risk of developing lung cancer among the smokers compared to non-smokers – Relative Risk (RR) and Odds Ratio (OR)

Module 9

Prediction model or identifying risk factors for some event of interest – e.g., what are the risk factors for cardiac surgery mortality?; how many glasses should you drink on Friday night? – do you know the risk factors of your blood alcohol level?

Module 10

Sample size calculation – how many patients should you recruit in your study?