Statistics II

Recommended Prerequisites

Knowledge acquired during the unit taught in the previous semester (i.e., Statistics I).

Teaching Methods

Theoretical classes (50%): Lectures about the concepts related to the methods and techniques of descriptive statistics and univariate and multivariate statistics. Practical classes (50%): to operationalize the conceptual dimension by solving problems using statistical software.

Learning Outcomes

This unit continues the teaching and learning goals of Statistics I. Specifically, we wish to deepen the statistical thinking (reasoning), to foster persistence in promoting the learning of statistics, and promote positive attitudes and beliefs (ex.: value) on the statistics usefulness in production and dissemination of knowledge about human behaviour.

We aim to develop practical skills of data analysis, in particular, using the program IBM SPSS Statistics. Students should be able to use a series of statistical inference procedures for intermediate and advanced level (ANOVA, Correlation, Regression, MANOVA) using either parametric or nonparametric tests, for analyzing experimental and correlational designs. In this unit, it is emphasized the acquisition of skills for effective analysis, under the general linear model, of the variability naturally occurring in psychosocial data.

Work Placement(s)

No

Syllabus

Theoretical concepts

 I. Introduction: GLM and data analysis

 II. Methods of Analysis of Variance (ANOVA)

 1. Univariate variance analysis (ANOVA with one fixed factor and independent groups)

 2. Factorial variance analysis (ANOVA with two fixed factors)

 3. Repeated measures variance analysis

 4. Mixed variance analysis

5. Repeated measures variance analysis with dual measurement

 6. Non-parametric variance analysis

 III. Methods of correlation and regression

 7. Correlation

 8. Simple linear regression

 9. Multiple Regression

 10. Analysis of Covariance

11. Analysis of multivariate variance (MANOVA)

 IV. Other topics of Statistics

 13. Alternative correlational techniques: partial correlation

 14. Data reduction techniques: Principal Component and Factor Analysis

 15. Main technical items analysis: Reliability of responses.

 

 B. Laboratories (using IBM SPSS Statistics in performing analysis and interpretation of the resulting outputs for each of the topics of the program)

Head Lecturer(s)

José Manuel Tomás Silva

Assessment Methods

Continuous
Two theoretical/practical tests: 100.0%

Final
Final exam: 100.0%

Bibliography

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

Field, A. (2005). Discovering Statistics Using SPSS (2nd 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. (2007). Análise estatística – Com utilização do SPSS (3ª ed.). Lisboa: Edições Sílabo.

Norusis, M. (2012). IBM SPSS Statistics 19 Statistical Procedures Companion. Upper Saddle River, NJ: Pearson.

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

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