On successful completion of the course, the candidate has:
Knowledge about
different types of recruitment procedures and randomization types
the assumptions of basic statistical analysis including simple linear regression analysis
strengths and limitations with respect to different quantitative research designs
Skills
can plan, conduct and evaluate different types of recruitment procedures and randomization types
can present descriptive statistics
can plan, conduct, interpret and evaluate results from basic statistical analysis including simple linear regression analysis
General competence
have an overview of different types of study designs and can independently plan, analyze, and interpret own and others results from basic statistical analysis
Course contents
Research designs
Population and research sample
Descriptive statistics; central tendency and dispersion tendency, level of measurements, statistical distributions
Comparison of two or more groups (t-tests (independent samples and paired samples), One-way ANOVA, Mann-Whitney, Kruskal-Wallis, Wilcoxon signed rank test, Chi-Square)
Association between variables (Pearson´s correlation coefficient, Spearman rank correlations, simple linear regression)
Teaching methods
Lectures combined with practical statistical exercises in a computer lab. Examples of analysis of data may be connected to the faculty’s on-going or planned research projects.
Examination requirements
Participation in compulsory lectures as stated in the course pamphlet.
Assessment methods and criteria
Individual 14-days home examination. The examination will be assessed as pass/fail.