Statistics and Data Analysis for Human Biologists

Course content

The course participants will be introduced to the fundamentals of statistical reasoning. They will learn how to apply appropriate statistical methods for common laboratory experiments, clinical trials and observational studies. During the course the student is required to work on an assignment(s) that will be handed in and presented on the last day of the course.

Education

MSc Programme in Human Biology - compulsory

Learning outcome

After completing the course the student is expected to:

Knowledge

  • describe the role of descriptive statistics and refer to appropriate statistical summary measures for different types of data
  • explain the mechanism of statistical inference, and refer to confidence interval and p-value for drawing evidence-based conclusions
  • rephrase statistical significance and statistical power in the context of a given laboratory experiment
  • understand the basic idea of how to design and carry out a study where data are collected and conclusions are based on statistical analysis of the data
  • reflect on limitations of the conclusions obtained with respect to study design, measurement error and sample size 
     

Skills

  • planning and design of an experimental study
  • communicate results of statistical analysis
  • present subject matter hypotheses and data
  • argue for the selected statistical methods 
  • discuss the statistical results 
     

Competencies

  • critically review public reports
  • review all steps from study design, data collection to subject matter conclusion
  • learn from the limitations of the own study to motivate follow-up studies

Lecturers and practicals

  • Lecture notes published in Absalon
  • Introduction to Statistical Data Analysis for the Life Sciences Claus Thorn Ekstrom, Helle Sørensen, 2010 Taylor and Francis

 

Note that the course is developed specifically for human biologists. This means that the examples used for illustration and the homework assigment may be difficult to follow for non-biologists.

ECTS
2,5 ECTS
Type of assessment
Course participation
Approval of assignment including oral presentation
Participation in minimum 80% of lectures and training activities
Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
One internal examiner
Criteria for exam assessment

To achieve a course certificate, the student must be able to:

Knowledge

  • describe the role of descriptive statistics and refer to appropriate statistical summary measures for different types of data
  • explain the mechanism of statistical inference, and refer to confidence interval and p-value for drawing evidence-based conclusions
  • rephrase statistical significance and statistical power in the context of a given laboratory experiment
  • understand the basic idea of how to design and carry out a study where data are collected and conclusions are based on statistical analysis of the data
  • reflect on limitations of the conclusions obtained with respect to study design, measurement error and sample size 
     

Skills

  • planning and design of an experimental study
  • communicate results of statistical analysis
  • present subject matter hypotheses and data
  • argue for the selected statistical methods 
  • discuss the statistical results 

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 15
  • Class Instruction
  • 15
  • Preparation
  • 39
  • English
  • 69