The module gives an introduction to factor analysis and develop statistical methods knowledge in the areas of analysis of variance and multiple regression analysis. In addition, there will be an introduction to the principles of constructing psychological measurement scales. The module puts an emphasis on actually using the various methods through a case-based approach, where the presentation and interpretation of results from analysis will be practiced thoroughly.

The module gives an introduction to factor analysis and develop statistical methods knowledge in the areas of analysis of variance and multiple regression analysis. In addition, there will be an introduction to the principles of constructing psychological measurement scales. The module will put an emphasis on actually using the various methods through a case-based approach, where the presentation and interpretation of results from analysis will practiced thoroughly. The specific statistical methods are related to the following: latent variables, factor analysis, linear and curvilinear effects in regressions, analysis of variance, mediation and moderation analyses. Overalll, skills in running, testing for measurement scales as well as reporting these methods are practiced.

On successful completion of this module, students will be able to: - demonstrate their knowledge of the principles behind operationalizing latent variables and formal concepts - demonstrate their knowledge of the principles behind the estimation of factor loadings and the rotation of latent factors - demonstrate their knowledge of the principles behind the coding of linear and curvilinear effects - demonstrate their knowledge of the principles of testing mediation and moderation - Formulate questions for self-report scales and determine their scoring (determine measurement level and answering categories) - Run exploratory factor analyses and interpret and present their results - Test one- and multidimensionality in measurement instruments, especially through the use factor analysis - Display skills in running factor analyses, including the ability to determine the number of factors, interpret factors found in a factor analysis, and create factor scores. - Conduct multiple linear regression analyses and interpret the results from the analyses. - Display skills with multiple regression, including knowledge of curvilinear effects, mediation analysis, and moderation analysis. - Use variance analyses to determine differences between groups and change within groups over time, and interpret and results from the analyses - Use this knowledge practically in the form of SPSS exercises and by solving various practical problem cases involving these skills. - Demonstrate their knowledge in presenting statistical results in line with established APA standards. - Display general competence in constructing and evaluating psychological measurement instruments. - Display general competence in interpreting and presenting results from multivariate analyses in general.

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This is an advanced methods and analysis module, thus certain prerequisite knowledge is required: Descriptive statistics (averages, variance, standard deviation, covariance, correlation) Statistical tests of hypotheses Estimation of reliability, in particular through calculating Cronbach's alpha Linear regression analysis using one and two independent variables Use of t-test and analysis of variance (one-way, univariate) to compare groups If students do not have this knowledge, it will be necessary that they acquire it through self-study before the course starts. It is recommended for everyone to refresh their knowledge before the course. The module is delivered in 2h lectures twice per week, and 2 hour tutorials. Assessments are done with individual coursework.