Course Basic Biostatistics - part 1

ECTS: 3.4

Course leader: Erik Thorlund Parner

Language: English

Graduate school: Faculty of Health

Graduate program: PH

Course fee: 4,080.00 DKK

Status: Course is finished

Semester: Fall 2023

Application deadline: 09/08/2023

Cancellation deadline: 23/08/2023

Course type: Classroom teaching

Start date: 06/09/2023

Administrator: Anne Fabricius

Waiting list

Applicants are initially placed on a waiting list. Seats are allocated ad hoc up until the application deadline. Seats are offered to applicants who meets the course prerequisites, and according to standard course seating rules.

Entry requirements

You must have participated in and passed the course C119/ Datamanagement & Stata prior to this course.

The course P1050/40 

Basic Biostatistics Part 1 is being offered by the Graduate School of Health, Aarhus University, spring 2023.

NB! If you are enrolled per 1 May 2015 or after, "Basic Biostatistics" will no longer be mandatory. Thus, it is up to you to agree with your main supervisor whether or not you should participate in "Basic Biostatistics".

Please note that participating in PhD courses on advanced statistical topics including Statistical Analysis of Time to Event Data, Linear regression models for continuous and binary data, Analysis of variance and repeated measurements and Applied Statistical Analysis with Missing Data requires completion of ‘Basic Biostatistic’ part 1 and 2 (former known as ‘Basic Biostatistic’ (8 days)) or similar.

ECTS for the courses Biostatistics part 1 and part 2 ARE NOT INCLUDED in the ECTS calculation of the course calendar, but will, of course, be included in your total ECTS obligation.
Therefore, the courses Biostatistics part 1 and part 2 will not prevent you from taking more courses in PhD Course Management.

Criteria for participation: University degree in medicine, dentistry, nursing, or Master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Prerequisites: It is mandatory that you have participated in and passed the course C119/ Datamanagement & Stata prior to this course. 

The course material is based on the statistical package Stata and R. The participants should expect to spend some time each week preparing for the course lectures and working on the exercises. Reserve 1.5 additional day each week for this.

Aim: The course provides the students with basic skills using the most common, simple statistical models and analyzes in medical research.

Learning outcomes:

  1. Document and handle data needed for a statistical analysis
  2. Chose a relevant statistical model for a given research question and evaluate the assumptions of the statistical analysis
  3. Perform a statistical analysis based on the chosen model
  4. Describe the results of the statistical analysis, and discuss the results in relation to the scientific question
  5. Make simple calculations of sample sizes for the planning of a comparative study

Workload: The full workload of the course is expected to be 84 hours. 

Content: Basic statistical concepts such as mean, standard deviation, model, estimate, test, p-value, and confidence interval. One and two sample problems, paired data. Non-parametric methods. The binomial distribution, and analysis of cross tabulated data. Model diagnostics. Power and sample size calculations.

Instructors: Professor Erik Thorlund Parner

Venue: 

Theory: Ole Worms Allé, 8000 Aarhus C

Exercises: Victor Albeck building, 8000 Aarhus C.

We recommend that you bring your own laptop.

Participation in the course is without cost for:

  • PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
  • PhD students enrolled at partner universities of the Nordoc collaboration
  • PhD students from other institutions in the open market agreement for PhD courses

 

 

Course dates:

  • 06 September 2023 09:15 - 16:00
  • 13 September 2023 09:15 - 16:00
  • 20 September 2023 09:15 - 16:00
  • 27 September 2023 09:15 - 16:00