Statistical Methods: Advanced Topics

Recommended Prerequisites

Mastery of the contents of Statistical Methods: Fundamentals.

Teaching Methods

Lecturing is mostly used for teaching the syllabus contents in the theoretical classes.

Demonstrating and collaboration methods will be mainly use in the lab classes.

Learning Outcomes

This c.u. gives continuity to the learning-teaching objectives settled for the curricular unit of Statistical Methods: Fundamentals. Specifically, it is aimed to deepen statistical thinking (reasoning), foster persistence in statics learning, and promote attitudes and positive beliefs (e.g., value) concerning the usefulness of statistics in the production and dissemination of knowledge about human behavior.  We strive to develop practical skills of data analysis, namely by using IBM SPSS Statistics program. Students should be able to use a range of intermediate and advanced inferential statistical procedures (ANOVA, Regression, MANOVA, ANCOVA) by using parametric and non-parametric tests to analyze experimental and correlational designs.  This unit emphasizes the acquisition of effective skills to analyze, within the general linear model, the variability that naturally exists in psychosocial data.

Work Placement(s)

No

Syllabus

A - Theorectical concepts

1. GLM - Factorial analysis of variance (ANOVA): completely independent designs, completely related designs and split-plot designs.

2. Multiple linear regression: standard and hierarchical.

3. Logistic regression.

4. Analysis of covariance (ANCOVA).

5. Multivariate analysis of variance (MANOVA).

6. Non paraetric tests: two independent/related samples.

7. Univariate non parametric ANOVA: independent/related samples.

8. Chi-square: one categorial variable and contigency tables.

B - Laboratories

1. Using the appropriate SPSS menus and programming for implementing and obtaining the outouts associated with the above topics.

Head Lecturer(s)

José Manuel Pacheco Miguel

Assessment Methods

Assessment
Frequency: 100.0%

Bibliography

Cohen, B. (2008). Explaining Psychological Statistics. Hoboken, NJ: Wiley.

Field, A. (2013). Discovering Statistics Using SPSS (4nd ed.). London: SAGE.

Glass, G. V., & Hopkins, K. D. (1996). Statistical Methods in Education and Psychology (3rd ed.). Boston: Allyn & Bacon

Howell, D. (1997). Statistical methods for psychology (4ª Ed.). Belmont, CA: Duxbury Press.

Maroco, J. (2011). Análise estatística – Com utilização do SPSS (5ª ed.). Lisboa: Edições Sílabo.

Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). New York, NY: Routledge.

Pallant, J. (2010). SPSS survival manual: A step by step guide to data analysis using SPSS (4th ed.). Maidenhead: Open University Press/McGraw-Hill.

Pestana, M. H., & Gageiro, J. N. (2008). Análise de Dados para Ciências Sociais - A complementaridade do SPSS (5ª ed.). Lisboa: Edições Sílabo.

Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics (5ª ed.). Boston: Allyn and Bacon.