FHE4110 ¨C Fundamentals in Data Management and Statistics

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 to the course

This course is only available for students at the following master's programmes:

• Folkehelsevitenskap og epidemiologi (master)
• International Community Health (master)

Students at Folkehelsevitenskap og epidemiologi (master) have priority.

There are 10 available seats for students at International Community Health (master)

If there are more than 10 applicants from International Community Health, the principle of the first come, first served applies.

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for?in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about?admission requirements and procedures.

Recommended previous knowledge

• INTHE4020 ¨C 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.

Examination and Grading at The Faculty of Medicine

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.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.