Schedule of Events
Statistical Methods for Research [E-LEARNING]
You can access the e-learning from September 30, 2024 until December 19, 2024.
Statistical Methods for Research is targeted at young scientists who require a foundation course in statistics, specifically in the quantification of variability, providing students with the practical techniques they will need to conduct statistical analysis at postgraduate level and beyond. This course takes a cross-disciplinary approach and is compatible with all major statistics packages such as SPSS, GenStat, Minitab and Stata. It is rich with scenarios, worked examples, practical applications and interactive statistical models.
The course comprises the presentation of concepts, individual computer-based exercises for consolidation and other interactive learning activities. A major component of the course is analysing data through the use of mainstream statistics packages. This will enable students to gain statistical skills commonly used today in evidence-based decision making, driven by data gathered during the research process, such as the use of estimates, confidence intervals and hypothesis tests, and the building of statistical models. The following four areas are included in the course:
• Describing data well: Descriptive statistics
• Making good generalisations: Inferential statistics
• Formulating and testing statistical hypotheses
• Fitting appropriate statistical models and interpreting their output.
The course contains different tracks for the disciplines of Engineering, Natural Sciences, Biomedical Sciences, Social Sciences and Business.
Statistical Methods for Research is based on a highly successful course from the University of Reading which has recorded an average improvement of 125% in student’s performances.
Duration of this course: 12,5 h
The indicated course duration refers to the pure review of the learning content. Please plan additional time for working on exercises and transfer tasks.
This e-learning course is being offered in a self-learning format. You therefore have the option to begin at any time convenient to you and work through it at your own pace.
Please note
You can register below, we will then check your application. If you are a KHYS member, you will receive the login details as well as further information on the course in a separate e-mail approximately two to three weeks after your registration. You will be able to access the e-learning on an online training platform of KIT.
This workshop is open to doctoral researchers and postdocs at KIT who are KHYS members.
For its members, KHYS covers the costs that incur for holding this event.
Dr. Claire Earnshaw
Karlsruhe House of Young Scientists (KHYS)
Karlsruher Institut für Technologie (KIT)
Straße am Forum 3
76131 Karlsruhe
Tel: +49 721 608-47042
Fax: +49 721 608-46222
Mail: weiterbildung ∂ khys kit edu
https://www.khys.kit.edu
Registration is required for this event. You can register online here.
Online Registration