STV2020 – Social Science Data Analysis and Programming
Course content
The course offers an introduction to programming-based problem solving for social scientists. With ongoing digitalization in the public sector and automation of services, digital competence is in demand among employers in both the public and private sectors.
The course introduces a number of problems and solutions in social science data processing with applications in R. We start with a number of general programming topics, followed by efficient processing of different data structures and how data can be combined using SQL and Tidyverse. Secondly, we look at special challenges related to space and time. The spatial dimension introduces GIS techniques. Towards the end, we see how machine text analysis can be used to automate data collection and we look at how we can effectively visualize different types of data.
The course provides a good basis for independent work with social science information.
Learning outcome
Having concluded this class students will:
Knowledge
- Efficiently process different types of data
- Be able to write R code
- Master the whole online process from data collection via analysis to visual presentation
- Be able to define a research problem that can be answered by information available online
Skills
- be familiar with programming in R, and use data structures, write loops and more efficient options, do condition tests and write your own functions
- be able to write R-code that retrieves data from web pages, analyze these and present the results using tables and figures
- be able to make an interactive presentation of your research results
General competence
- know how to collect, prepare, analyze and present relevant data to answer social science questions
Admission to the course
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.
Formal prerequisite knowledge
STV1020 – Politisk analyse 2: 澳门皇冠体育,皇冠足球比分sdesign og kvantitative metoder or other introductory course in research methods and statistics
Teaching
Lectures and seminars
Compulsory activities
This course has mandatory teaching and requires physical presence at seminars.
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Attend at least three of the five seminars
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Students are required to submit three mandatory hand-ins, which should be written up using Quarto
The seminars are taught in English, and the R scripts handed in must be commented in English.
See the faculty`s rules for reassignment of seminar groups and requirements for compulsory activities.
Absence from compulsory activities
If you are ill or have another valid reason for being absent from compulsory activities, your absence may be approved or the compulsory activity may be postponed.
A student who has completed compulsory instruction and coursework and has had these approved, is not entitled to repeat that instruction and coursework, and does not have to in order to retake the exam.?If a student have only partially approved compulsory activities, they must complete those again to take a new exam, along with any other compulsory activities they haven't yet passed. A?student who has been admitted to a course, but who has not completed compulsory instruction and coursework or had these approved, is entitled to repeat that instruction and coursework, depending on available capacity.
Examination
Term paper
You must have passed the compulsory activities in order to sit the exam
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Examination support material
All support material is allowed. When using AI, you must explain and be transparent about its use: read more about the guidelines for AI and exams at?How to use AI as a student - University of Oslo
Language of examination
The examination text is given in English, and you submit your response in English.
Grading scale
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- 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.