SHUA13024U  Statistics and Data Analysis for Human Biologists

Volume 2018/2019
Education

MSc Programme in Human Biology - compulsory

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. 

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

  • power and sample size calculation for 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
  • Lecture notes published in Absalon
  • Introduction to Statistical Data Analysis for the Life Sciences Claus Thorn Ekstrom, Helle Sørensen, 2010 Taylor and Francis
Lectures and practicals.
Individual
Continuous feedback during the course of the semester
Credit
2,5 ECTS
Type of assessment
Written assignment, 48 hours
Take-home exam (Digital Exam). Students upload a pdf file.
Exam registration requirements

None

Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
One internal examiner
Exam period

See the exam plan

Re-exam

See the exam plan

Criteria for exam assesment

To achieve the grade Pass, 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

  • power and sample size calculation for an experimental study
  • communicate results of statistical analysis
  • present subject matter hypotheses and data
  • argue for the selected statistical methods 
  • discuss the statistical results 
  • Category
  • Hours
  • Lectures
  • 15
  • Class Instruction
  • 15
  • Preparation
  • 23
  • Exam
  • 16
  • Total
  • 69