Statistics / Development Psychology

Teaching Methods

Being guided by the know-how principle , this curricular unit privileges theoretical and practical classes: strategies and diverse activities will be used, for instance lectures, interactive lectures, discussion and group work , problem solving and data analysis (using statistic softwares) and the critical analysis of the implementation of several of the techniques taught.

Learning Outcomes

This cu has the main objective of improving the research competences, providing the students with more knowledge, reviewing and introducing new concepts and techniques the data analysis practice. In the end of this unit, students should be able to: choose between different strategies, in accordance with the investigation objectives and issues; define and draw an investigation strategy, recognizing the steps it should contemplate; use the statistic language in a clear and proper way; understand the data analysis in the reading of scientific articles; understand the basic concepts, models, assumptions, advantages and limitations of the multivariate data analysis techniques addressed in the cu; choose between the different analysis techniques; understand and implement the data analysis techniques addressed in the curricular unit; use ICT reference tools in the data analysis with the addressed techniques; interpret the obtained results with the implementation of those techniques.

Work Placement(s)

No

Syllabus

Introduction to statistic software SPSS

. Univariate exploratory data analysis

. Parametric tests to compare populations

. Non-parametric tests to compare populations

. Bivariate exploratory data analysis: association vs. correlation

. Methods of multiple linear regression

. Methods of factorial analysis

. Methods of grouping analysis

. Trajectory analysis: the PLS algorithm.

Assessment Methods

Evaluation
Critical analysis of an article: 50.0%
Data analysis work : 50.0%

Bibliography

Howell, D. C. (2008). Fundamental Statistics for the Behavioral Sciences (6th ed.). Canada: Thomson Wadsworth.

Robson, C. (2002). Real world research (2nd ed.). Oxford: Blackwell.

Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Allyn & Bacon.