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.
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
- 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
Teaching and learning methods
Lectures and practicals.
Literature
- Lecture notes published in Absalon
- Introduction to Statistical Data Analysis for the Life Sciences Claus Thorn Ekstrom, Helle Sørensen, 2010 Taylor and Francis
Feedback form
Individual
Continuous feedback during the course of the
semester
Sign up
This course is not available for credit transfer students and other external students.
Exam (SHUA13024E)
- ECTS
- 2,5 ECTS
- Type of assessment
-
Written assignment, 48 hours
- Type of assessment details
- 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
Criteria for exam assessment
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
Workload
- Category
- Hours
- Lectures
- 24
- Class Instruction
- 6
- Preparation
- 23
- Exam
- 16
- English
- 69
Kursusinformation
- Language
- English
- Course number
- SHUA13024U
- ECTS
- 2,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 4
- Schedulegroup
-
See Syllabus
- Capacity
- 40 participants
- Studyboard
- Study Board for Human Biology, Immunology and Neuroscience
Contracting department
- Department of Public Health
Contracting faculty
- Faculty of Health and Medical Sciences
Course Coordinator
- Erin Evelyn Gabriel (12-6f7c737838716b6c7c736f764a7d7f786e38757f386e75)
Teacher
Mia Klinten Grand course responsible by August 2021
Saved on the
12-04-2024
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