Introduction to Statistical Modelling with R

TitleTimeRoomTeacher
Introduction to Statistical Modelling with R17.04.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R24.04.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R15.05.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R22.05.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R29.05.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R12.06.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R19.06.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R26.06.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R03.07.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R10.07.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Introduction to Statistical Modelling with R17.07.2026 13:30 - 15:00 (Fri)Graduate Center of Life Sciences, Seminarroom 1st. floor, Alte Akademie 8a, 85354 FreisingDr. Tina Köhler
Keywords: 
R, coding, programming, univariate statistics, multivariate data analysis
Course Description: 

Topics covered in the course include using the programming language R and the software RStudio, probability theory, estimation, hypothesis testing, confidence intervals, linear models; generalized linear models; mixed models, descriptive statistics and data visualization.

Course aims: 

      Students will be able to use R for their data analyses and gain a general understanding for the logic of coding to be able to use similar programming languages as well (e.g., python).

      Students will have practically-oriented knowledge about data handling, including the analysis and graphical presentation of data, as well as simulation using the programming language R, which is the de facto standard for statistical data analysis software.

      Students will be able to understand basic concepts of statistics, to choose appropriate statistical methods to answer common environmental and ecological questions, to apply these methods in R and to interpret the results correctly.

Teaching methods: 

The module is constructed as an exercise (UE) to learn (1) using R as a programming language to (2) analyze environmental and ecological data in a statistically meaningful way. Introductions to theoretical concepts will alternate with individual practical applications of the learned material to promote hands-on, practical learning.

This course fits doctoral candidates in the following phase: 

☒ Beginn der Promotion / Beginning of the doctorate
☒ Während der Promotion / During the doctorate
☐ Endphase der Promotion / End of the doctorate

Participation requirements: 

None

Technical requirements: 

Personal laptop 

Course preparation: 

None

Additional information: 

Topics covered in detail:

·       Working with R: Introduction, basic operators

·       Working with R: Vectors, matrices, data frames, lists

·       Working with R: Working space, reading and writing external data

·       Working with R: Creating and exporting plots

·       Working with R: Loops (if & else, for)

·       Introduction to statistics, probability

·       Correlations and linear regression

·       Hypothesis testing: classical tests, p-value, ANOVA

·       Multiple regressions

·       Linear mixed effect models

Introduction to the analysis of multivariate data

Category: 
Fachspezifische Veranstaltung
Event type: 
Seminar/Workshop
Organizer: 
Graduate Center of Life Sciences
Responsibility for event: 
Hauptverantwortung
Format: 
In Präsenz
Course Language: 
EN
Course Capacity (Max): 
15
Course capacity (Min): 
5
Duration in hours: 
16
Trainer: 
Dr. Tina Köhler

I am a soil-plant hydrologist working at the interface of soil physics, plant physiology, and ecohydrology. My research focuses on physical properties and processes in plants and the critical zone that determine how plants regulate their water use under complex environmental stress. I study these dynamics across multiple spatial and temporal scales, from organ-level processes to single-plant responses and field-scale patterns. I combine multiscale experimental approaches, from controlled environments to field trials, with soil-plant hydraulic and structural-functional modeling. Ultimately, my aims are to address food security issues, and to contribute towards refining models of terrestrial carbon, water, and energy fluxes, where plant water use regulation plays a central role in coupling land–atmosphere processes.