Course description

• Course content
• Learning outcome
• Admission
• Prerequisites

• Teaching
• Examination
• Evaluation

Course content

The course will give fundamental knowledge and experience with methods and tools for data collection, quality checks, data structures, preparation of data for analyses and statistical methods.

Learning outcome

Knowledge 
Upon completion of the course the student should be able to:  

• describe how different variable types (strings, numeric) can be used in analyses  
• explain precision and validity of variables and how it can affect choice of data collection method
• explain the difference between statistical significance and clinical relevance  
• explain what do p-values and confidence intervals really tell us and what is Type 1 and Type 2 errors  
• describe the process of developing and validating questionnaires for use in scientific data collection 
• explain the strengths and weaknesses of presenting results as absolute and relative differences

Skills 
Upon completion of the course the student should be able to:  

• use tools for data collection  
• transform datasets between long and wide formats  
• merge data from different sources  
• document their work with data management and data analysis using syntax  
• explore datasets to detect potential errors and extreme values, variables of poor quality such as individuals with excess missing data, variables with contradictory information, duplicates, missing ID number, impossible values etc.  
• define exposures, outcomes and auxiliary variables in data sets  
• analyze data with different designs, and present results on absolute and relative scale  
• analyze data with appropriate univariable and multivariable linear and logistic regression models
• create tables and figures using STATA  
• provide and receive peer feedback on data syntax and analytical strategies

General competence 
Upon completion of the course, the student should have acquired and developed:  

• an understanding of how definitions of variables and data that occur during the design phase of a research project, data collection, data preparation and analysis can influence the study results 
• an understanding of the value of providing and receiving feedback from peer students

Admission

This course is only available for master students at Folkehelsevitenskap og epidemiologi (FHE), and International Community Health (ICH). Students at FHE and ICH must apply for this course in Studentweb.

• Students at Folkehelsevitenskap og epidemiologi have priority
• There are 10 available seats for students at International Community Health. If there are more than 10 applicants from International Community Health, the principle of the first come, first served applies.
   

Prerequisites

Recommended previous knowledge

• INTHE4020 - Introduction to Quantitative Methods; or equivalent
• INTHE4021 ¨C Introduction to Epidemiology; or equivalent

Teaching

• Student mentoring, peer-review for syntaxes and data analysis. 
• 25% lectures  and 75% training (Hands-on).

Examination

Home exam, individual.

Grading

The Board at the University of Oslo has decided to introduce detailed guidelines for all examinations, which take place at the University. The description of the grading should be clear and transparent. This is done to ensure alignment between learning outcomes, assignments, and grading. The Faculty of Medicine has developed a web page with information regarding exams and the grading procedures. 

Submit assignments in Inspera

You submit your assignment in the digital examination system Inspera. Read about how to submit your assignment.

Use of sources and citation

You should familiarize yourself with the rules that apply to the use of sources and citations. If you violate the rules, you may be suspected of cheating/attempted cheating.

Language of examination

The examination text is given in English.You may submit your response in Norwegian, Swedish, Danish or English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Explanations and appeals

• Explanation of grades and appeals

Resit an examination

• Illness at exams / postponed exams
• Resitting an examination

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Evaluation

The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.