R is one of the most widely used software for statistics and data science. In this course, the students will have the chance to become familiar with basic R objects, operations, visualizations tools and programming. The course will have in-class and online components. The online material (more information here: http://www.uta.fi/cast/events/Ronline.html) should be done before the first day of the course or between the two in-class days of the course. The second in-class day of the course will offer the chance to get a deeper knowledge about R and to analyze own data.

Modes of study: pre-assignment, participation in course work

BOTH online and in-class parts are required for the completion of the course.

 Pre-assignment: Please write a short (half A4) text stating:

1)    Your name & disciplinary background

2)    State your own motivation for participating on this course and what do you expect to learn.

Maximum number of students is 20. Priority will be granted for the first enrolments, based on the proportions: 60% PhD students 30% MSc students and 10% BSc students. Students should check the selection result via NettiOpsu after the enrolment period.

Multilevel models are designed to explore and analyse data that come from populations which have a complex structure. Behavioural and social data commonly have a nested structure. Multilevel models are becoming an increasingly popular method of analysis for situations where responses are grouped, such as in schools or other institutions, neighbourhoods, firms, parliamentary constituencies, or any other social or spatial clusters. A particular version of multilevel modelling is where there are multiple measures on each respondent, so that the grouping is of measures within person; where these multiple measures are taken on successive occasions, multilevel modelling provides a means of modelling individual change over time. This course will emphasise the practical application of multilevel models and lectures will be combined with practical sessions in order to reinforce concepts.

Course contents

• Duration (2 days)
• Lectures (6 h)
• Hands-on exercises with MLM tools (6 h)

Flash presentation on application of MLM in participant’s own research or field (5-10 minutes each)

Target group
The course is intended for post-graduate candidates and researchers who are interested in the use of multi-level modelling in their research. Understanding of basic statistics is required.

Enrolment: At the maximum 24 students. Priority will be given to those who need MLM in their research (PhD researchers most especially).

For pre-selection evaluation, please write a short text stating:

• Your name and disciplinary background
• Your motivation for participating in the course and what you expect to learn