STV2020 – Social Science Data Analysis and Programming

Schedule, syllabus and examination date

Choose semester

Course content

Changes spring 2021 due to coronavirus: 

This course is planned with physical lectures and physical/digital seminars. There will be a digital alternative for the lectures. For information on which seminar groups are physical/digital see the schedule. Be aware of possible changes.

All students who requires a digital seminar alternative will get this, but we can not guarantee place on physical seminars. You can change seminar group at Studentweb from 4. January, or you can use the required form.

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

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.

This course is only available for students enrolled in the Political Science bachelor program. 

Prerequisites

Recommended previous knowledge

STV1020 – Metode og statistikk or other introductory course in research methods and statistics

Teaching

Lectures and seminars

Compulsory activities

  • Students are required to upload an R script in Canvas after at least 3 seminars

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.

Examination

Term paper.

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, 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.

Explanations and appeals

Resit an examination

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Facts about this course

Credits

10

Level

Bachelor

Teaching

Spring 2021

Examination

Spring 2021

Teaching language

English