FLER4110 – Introduction to Statistical Analysis for Language Students
Course description
Course content
This course introduces students to fundamentals of statistical analysis of linguistic data. Students will learn the basics of statistical modeling with an emphasis on the (generalized) linear model framework. They will learn both exploratory techniques (such as descriptive statistics and data visualization) and hypothesis testing techniques such as linear and logistic regression within the null hypothesis significance testing framework. The entire course will use the open source softwares R and Rstudio. Importantly, students will also learn how to do data analysis in a way that is open and reproducible.
This class requires no prior statistical, mathematical, or coding background, but the content of this class is expected to serve as a solid foundation for more advanced statistical courses.
Learning outcome
Students will learn how to:
? understand fundamentals of statistical analysis
? use the statistical software R
? prepare data tables for further analysis
? visualize data
? explore data
? test hypotheses within the null-hypothesis-significance testing framework
? critically evaluate statistical results from published papers
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.
Prerequisites
Recommended previous knowledge
No specific prerequisites. If students decide to use R, they are expected to bring their laptops to classes for doing exercises and make sure that they have current versions of R and R-Studio on their laptops. SPSS is installed on university computers.
Overlapping courses
10 credits overlap with FLER2110 – Introduction to Statistical Analysis for Language Students (continued)
Teaching
2-hour classes for 14 weeks. The majority of classes will involve practical exercises with a computer to apply the knowledge acquired from the readings and self-study. One assignment will be offered every week. 8 assignments out of 12 (around 80%) will be needed to be completed and approved in order to be eligible to take the final exam.
Access to teaching
A student who has completed compulsory instruction and coursework and has had these approved, is not entitled to repeat that instruction and coursework. 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
An 8-hour home exam.
- The grading guidelines can be read at the Study Advisors office
Written examination
The written examination is conducted in the digital examination system Inspera. You will need to familiarize yourself with the digital examination arrangements in Inspera.
Read more about written examinations using Inspera.
Submission in Inspera
You submit your assignment in the digital examination system Inspera. Read more about how to submit in Inspera.
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
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.