Introduction to Epidemiological Analysis

Introduction to Epidemiology and Research Methodology:
Students who successfully complete this course, should be able to correctly:
1.Understand and correctly apply the basic tools of epidemiology and research
2.Identify various research designs, know their uses and limitations
3.Understand the basic principles of sampling and apply that knowledge to everyday investigations
4.Understand the basics of screening, sensitivity and specificity of tests
5.Recognise bias in the design of investigations and try to avoid it
6.Understand the epidemiology of disease clustering and outbreaks and how to investigate them
7.Be aware of the principles of causation
8.Be able to report on their findings professionally, both in writing and orally.
Introduction to R:
R is an open-source, statistical software platform that is growing in popularity due to its rapidly expanding number of libraries containing cutting edge statistical functions, as well as the user-friendly, built-in communication tools in RStudio. Course participants will build on their basic working knowledge of base R, and will learn good coding practice, import and clean data, the basics of analysing and visualising data, and reporting results. Specific topics that will be covered include ¿thinking code¿, importing and exporting data, cleaning/tidying data, joining datasets, dealing with dates and factor/categorical variables, and summarizing data using basic descriptive statistics, plots, and tables.