Aim and content

This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH.

Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee.

Aim

This five-day intensive course aims at Ph.D. students in biomedical research who work in a laboratory or similar setting, performing experiments on e.g. cells, tissues, mice, or human volunteers. When participating in this course, you will get a working knowledge of statistical concepts, methods of analysis, and adequate ways of presenting statistical results, as well as hands on experience in analysing experimental data with R statistical software. We will also explain some of the most common errors biomedical researchers make in their statistical analyses. In summary, we aim at teaching you high-quality statistics suitable for research publications.

Learning objectives

A student who has met the objectives of the course will be able to:
1. Have a qualified discussion with a statistical consultant, e.g. on how to plan the analyses for a research project or how to answer the concerns raised by a reviewer.
2. Interpret basic statistical information from research papers, e.g. descriptive statistics, effect estimates, confidence intervals and p-values.
3. Apply the most frequently used statistical analyses to real life experimental data using the statistical software R (see contents section for the specific analyses taught in this course).
4. Present statistical results in suitable figures, tables, and words.
5. Critically assess the validity of the most frequently used statistical analyses by being aware of their modelling assumptions and limitations.

Content

Day 1: The Scientific method, summary statistics and figures, distributions, and random variables

Day 2: One sample inference for the mean, Central limit theory, p-values, confidence intervals, type I and II error, and power.

Day 3: Comparing more than two groups/conditions for continuous outcomes, paired data, and simple linear regression, Comparing two or more frequencies: Risk difference, risk ratio, and odds ratios. The chi-square test and Fisher’s exact test and paired data

Day 4: Linear regression

Day 5: Generalized linear regression and introduction to causal inference.

Statistical software

We will be working with the open source statistical software R using the interface R Studio. To participate in the course you must bring your own laptop with R and R Studio installed.

Prerequisites

Familiarity with R programming is necessary for taking part in the exercise classes and for completing the homework problems. If you are not familiar with R programming, we recommend that you complete the free access e-learning course at http://r.sund.ku.dk/ before starting on this course.

Considering statistical theory, almost all of the students who participate in this course have completed a statistics course during previous education. For repetition and for emphasizing research applications, we start from scratch. However, you should be warned that we cover many topics in few days and at high pace.

Participants

Ph.D.-students. In case of vacant seats also other medical researchers. Max. 40 participants.

Relevance to graduate programmes

The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

All graduate programmes

Language

English

Form

Forum lectures and interactive learning for 3 hours in the morning and computer exercises for 3 hours in the afternoon on course days 1-3 and 6,
Forum lectures and interactive learning for 3 hours in the morning on course days 4-5.

Course director

Associate professor Erin Gabriel, Section of Biostatistics

Teachers

Associate professor Erin Gabriel
Associate professor Michael Sachs, Section of Biostatistics

Dates

Mondays and Thursdays: 7, 10, 11, 21 and 24 October 2024, all days 10-17.

Course location

CSS

Registration: Please register before 5 August 2024

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.