### Biostatistics Using real examples from medical literature, this course introduces clinical research and applied statistics.  It also prepares learners to critically read and understand medical literature.

After completing this course, participants should be able to:

• Describe the empirical cycle
• Differentiate between hypothesis-generating and hypothesis-testing studies
• Formulate a research hypothesis
• Identify the research hypothesis in a given study
• Identify the predictor and outcome in a given study
• Define target population, study population, and study sample
• Describe the different types of studies used in medical research
• Recognize the advantages and limitations of the different study designs
• Identify sources of bias in different study designs
• Describe the relative strength of each type of study design in establishing causality
• Describe sources of variation in medical data
• Differentiate between continuous and categorical data
• Define time-to-event data
• Define mean and standard deviation
• Identify how data were measured in real studies
• Describe how diagnostic tests are evaluated
• Define and calculate sensitivity, specificity, negative predictive value, and positive predictive value
• Describe sampling variation
• Formulate a null hypothesis
• Interpret a p-value
• Define type I and type II errors
• Differentiate between statistical and clinical significance
• Understand statistical power
• Interpret a confidence interval
• Describe the problem of multiple comparisons
• Describe the intention-to-treat principle
• Explain last observation carried forward
• Calculate odds ratios and risk ratios
• Interpret odds ratios, risk ratios, and hazard ratios
• Understand the results of simple statistical tests
• Recognize the names of more advanced statistical tests
• Identify the appropriate statistical test for a given study design and type of data
• Understand common pitfalls in medical statistics