Statistics for Biomedical Scientists

17-19th October 2018

This course will introduce participants to the basics of statistics on a more intuitive way without being encumbered by equations. This introductory course is to foster an appreciation for the role of statistics and associated data analysis approaches in research and in our everyday lives.

Aim of the course

To provide an introduction to biostatistics by explaining statistical principles with a focus on the scientific interpretation of statistical tests rather than on the mathematical logic of the tests themselves.

By the end of the course, the participants should be able to:

• Describe the main terms of descriptive statistics
• Explain the p-value and its meaning
• Explain the problem of multiple testing
• Discuss the tests to account for multiple testing
• Perform the main statistical test on a data set
• Describe the Bayesian statistics

Target group

PhD candidates in the beginning of their PhD trajectory; group is limited to 20 participants

Prerequisites

Working knowledge of English; basics knowledge of statistics, probability theory and combinatorics; basics knowledge of one of the programming languages (preferably Perl)

Duration of the course and a workload

3 days; 3 days x 8 hours per day = 24 hours

Location

GIGA B34 +5

Educators

Prof. Michel Georges (GIGA, ULiège)

Course Syllabus and Schedule

Day 1: Statistical significance

9:00-18:00. 12:30-13:30 - Lunch break

• Definition of p-value and confidence intervals
• Permutation tests
• Bootstrapping
• Accounting for confounders

Day 2: Multiple testing

9:00-18:00. 12:30-13:30 - Lunch break

• Multiple testing: the issue.
• Adjusting the thresholds
• Exploiting the p-value distribution: false discovery rate

Day 3: Advanced topics

9:00-18:00. 12:30-13:30 - Lunch break

• Likelihood based tests
• Bayesian statistics