Title | Time | Room | Teacher |
---|---|---|---|
Introduction to Sampling & Hypothesis Testing | 20.04.2023 15:00 - 18:00 (Thu) | online | Dr. John Pinney |
Course Description:
Introduction to the course topics:
This course provides an introduction to the statistical theory of sampling, parameter estimation and hypothesis testing in R. No prior programming experience is required.
Syllabus:
- random variables and distributions
- sampling distribution
- central limit theorem
- standard deviation versus standard error
- confidence intervals
- hypothesis testing
Course aims:
- Identify different statistical distributions
- Recognise sampling constraints and variability
- Employ skills to build confidence intervals
- Apply correct test statistics for hypothesis testing
- Assess numerical results to make statistical inferences
Participation requirements:
none
Technical requirements:
Laptop/tablet with stable internet connection, microphone, webcam, MS Teams
Additonal information, notes:
Please note that this course is offered in cooperation with the Imperial College London. Joining instructions for the course will be provided on booking.
Category:
Fachübergreifende Veranstaltung
Event type:
Seminar/Workshop
Organizer:
Graduate School Geschäftsstelle
Responsibility for event:
Hauptverantwortung
Format:
Digital/Online
Co-Organization:
Sonstige (Other)
Course Language:
EN
Course Capacity (Max):
7
Course capacity (Min):
1
Duration in hours:
3
Financial contribution:
15 Euro
Trainer:
Dr. John Pinney
Dr. John Pinney is Royal Society University Research Fellow in the Theoretical Systems Biology group at Imperial College London. More info here