Introduction to Statistics and R
Abstract
This course offers a practical introduction to the fundamentals of data analysis and R.
Objective
To acquire the statistical understanding to design an appropriate analysis and the practical skills to implement the analysis in R and present the results.
Content
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.
Literature
- external page Introductory Statistics with R: P Dalgaard
- external page Statistics: An introduction with R: MJ Crawley
- external page R for Data Science: G Grolemund and H Wickham
- external page An Introduction to Statistical and Data Sciences via R: C Ismay and AY Kim
Course Details
Information
All lectures will be given in English and are accompanied by a homework project every week. For each lecture, a set of exercises will be given that is relevant to the topic of the lecture and can be found in lecture material below. Solving and understanding the mathematical problems and programming exercises is an integral part of the course and will help in preparing for the graded examinations, as well as counting for 50% of the final grade. Solutions are due the following week and should be emailed to
Lecture Material
All lecture slides and exercises can be found here:
The password is "isar2021!".