This course offers a practical introduction to the fundamentals of data analysis and R
To acquire the statistical understanding to design an appropriate analysis and the practical skills to implement the analysis in R and present the results.
Data analysis is fundamental for arriving at scientific conclusions and testing different hypotheses. This course offers a hands-on introduction to statistical analyses including: exploratory data analysis, testing differences in populations, p-values, power calculations, multiple testing, confounding, linear regression, maximum likelihood, model selection, and logistic regression; along with the fundamentals of R programming including markdown and data handling with the tidyverse.
Lecture slides will be available
Prerequisites / Notice
Access to Rstudio with some markdown and tidyverse packages installed.