SHUA11011U Statistics and Data Analysis for Human Biologists

Volume 2015/2016
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. During the course the student is required to work on a project that is to be handed in for evaluation at the last course day.
 

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

  • apply basic steps of data management and analyse data in R
  • document the computer program which performs the data management and data analysis
  • test if results are replicable when applied to the same data
  • communicate results of statistical analysis, present subject matter  hypotheses and data, argue for the selected statistical methods, discuss the statistical results
     

Competencies

  • control the file structure behind a statistical analysis project
  • 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
None
Lecturers and practicals
  • Category
  • Hours
  • Class Instruction
  • 15
  • Lectures
  • 15
  • Preparation
  • 39
  • Total
  • 69
Credit
2,5 ECTS
Type of assessment
Course participation
Participation in minimum 80% of lectures and training activities
Approved project based on oral presentation
Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
One internal examiner
Criteria for exam assesment

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

  • apply basic steps of data management and analyse data in R
  • document the computer program which performs the data management and data analysis
  • test if results are replicable when applied to the same data
  • communicate results of statistical analysis, present subject matter  hypotheses and data, argue for the selected statistical methods, discuss the statistical results