PhD course

Place
IT University of Copenhagen
Rued Langgaards Vej 7; DK-2300 Copehagen S

Dates
spring term 2010 (detailed schedule to be announced)

Lectures
Irina Shklovski, Fiona Mulvey and Emilie Møllenbach

Time & Room
To be announced. Classroom at ITU

Organizers
Anne Hvejsel and Christina Neumayer, InC Group

Course description
Almost every PhD project needs statistics. This course should give anoverview on empirical and experimental methods and how to apply statistical analyses. ThePhD students will be introduced to statistics for analysing qualitative and quantitative dataand should be able to apply it to the design of their individual research projects. There willbe a special focus on descriptive statistics, experimental statistics, survey data analyses andmultivariate statistics. The students will use SPSS and get insights in research/methodologydesign, data definition/input, data modification, data analysis and data presentation. By theend of the course the students should be able to define their methodology design; enter, editand define data/variables; work on essential data modifications; carry out exploratory dataanalysis and interpret the results; work with SPSS. The aim of the course is to give insightsinto statistical analyses in regard to plan and carry out their research projects.

Prerequisites
PhD students should think about questions and problems about use of statistics in theirresearch projects.

Program

Pre-Meeting (2 hours; 2 weeks before course start):
PhD students can address their expectations and individual questions about the course.

Day 1:
Lecture 9-12 am
Group work 1-5 pm

Day 2:
Lecture 9-12 am
Group work 1-5 pm

Day 3:
Lecture 9-12 am
Group work 1-5 pm

Day 4:
Lecture 9-12 am
Group work 1-5 pm

Day 5:
Round-up, student presentations, questions 9-12 am
Round-up, student presentations, questions 1-5 pm

Credits
3 ECTS - (5 days – 1,5; preparation: 0,5; mandatory exercises: 1).

Exam:
Presentations, assignments

Amount of hours the student is expected to use on the course
Participation: 5 days (á 7 h) + pre-meeting (2 h)
Preparation: 15 h
Mandatory Exercises: 30 h

Participants
The course aims at PhD students who apply statistics in their PhD projects