Introduction to Statistics with R

Academia Raetica, University of Applied Sciences of the Grisons

General information and fee

  • Dates: March 9, 10 & March 25, 2022, ONLINE

  • Times: each date from 10:00-12:00, 13:00-15:00, and 15:30-17:30.

  • Lecturer: Prof. Dr. Andreas Nicklisch / FHGR

  • Language: English

  • Target audience: primarily PhD students, open to other interested scientists

  • Course fee for participants from Academia Raetica member or partner institutions: CHF 150. Registration deadline: Tuesday, March 8

  • External participants: CHF 250

  • Max. number participants: 12 (min. number participants 8)

  • Our terms and conditions

  • Course Coordinator: Daniela Heinen, daniela.heinen@academiaraetica.ch, phone 081 410 60 84

  • Credit points: This training requires 18 hours of attendance plus approximately 18 hours for preparation and homework. Please check with your supervisor at your university, if the course counts towards ECTS.

  • Course certificate: You will receive a certificate of attendance, if you attend the entire course.

Objectives

This course introduces the essentials of statistical analysis for students who have little or some background in statistics, but no programming skills in statistical software. Fundamental programming skills in R including analysis as well as (graphical) presentation are provided. Each block includes lectures and tutorials.

Course outline

Day 1

  1.  Introducing R

  2. Statistical interference
    – Mathematical priors
    – σ-algebra
    – Hypothesis testing
    – Densities and distributions
    – Moments of a distribution

  3. Single sample analysis
    – Convergence in distribution
    – Confidence intervals
    – Tests for point estimations

  4. Two-sample analysis
    – Two-sample moments
    – Parametric moment hypothesis tests
    – Non-parametric moment hypothesis tests

Day 2

  1. Regressions
    – Multiple linear regressions
    – Generalized regression models
    – Specification problems

  2. Time series analysis

  3. Panel data

Day 3

  1. Binary and categorical response data

  2. Count and proportional data

  3. Death and failure data

Material:

  • Crawley, M. J. (2014). Statistics: an introduction using R. Second Edition: John Wiley & Sons.

  • www.r-project.org

  • www.rstudio.com

About the trainer

Andreas Nicklisch is is a behavioral and experimental economist. Since 2016, he is a Professor for Economics and Statistics at the Center for Economic Policy Research at the University of Applied Sciences of the Grisons, Chur, Switzerland. His latest work is focused on behavioral institutional designs that enhance the cohesion of cooperation within societies, and the effect migration for social norms and values.

He graduated in Economics at the University of Jena, Germany, in 2002 and received his Ph.D. in Economics from the Max Planck Institute of Economics, Jena, in 2005. The same year, he joined the Max Planck Institute for Research on Collective Goods, Bonn, Germany, as a Research Affiliate. In 2010, he became Assistant Professor for Microeconomics at the School of Economics and Social Sciences of the University of Hamburg, Germany.


Image by G. Altmann / Pixabay

In order to optimize our website for you and to be able to continuously improve it, we use cookies. By continuing to use the website, you agree to the use of cookies. For more information about cookies, please see our Privacy policy.

Hide