Applied Quantitative Research Methods of Analysis

This is a course in quantitative methodology designed for professional education. The course prepares for design, data collection, and analysis of quantitative data. It combines theory and practical analysis of data using SPSS. Research ethics are dealt with in different parts of the course also privacy requirements. The course covers challenges related to operationalization, population, sample and generalization and various statistical analysis methods are reviewed.

Knowledge

The candidate

• can assess the strengths and weaknesses of various statistical methods
• can apply various statistical methods to empirical data
• has knowledge of statistical concepts and analysis techniques and can handle different and complex methodological questions related to validity and generalization

Skills

The candidate

• can prepare survey inquiries and conduct analyses of quantitative data sets

General competence

The candidate

• has the competence to carry out smaller research projects, which involve using quantitative methods, write scientifically about the project and the results and be able to use their skills to tutor candidates who use quantitative methods.
• has the competence to assess the quality of research based on quantitative data

The course is block-scheduled with lectures, discussions and work with statistical data on SPSS. Participants may use their own dataset or data provided by the course. The course will be practically oriented through analysis of own or borrowed data on SPSS. The lectures will to a large extent be based on exemplary experiences from our own analysis, combined with literature. The teaching will build up understanding and achieve knowledge goals through practical work with analysis, combined with supervision and lectures. The teaching will make little use of mathematics and practical arithmetic as basis for understanding. If the course has English-speaking students, the teaching will be in English. Assignments can be submitted in Norwegian or English.