Applied Statistics for Education

Recommended Prerequisites

Mastery of the contents of the discipline of Mathematics Applied to Social Sciences (MACS), taught in Secondary Education.

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 u.c. aims to deepen statistical thinking (reasoning), foster persistence in learning statistics and promoting positive attitudes and beliefs (e.g., value) about the usefulness of statistics in the production and dissemination of knowledge about educational behavior. We aim to develop practical data analysis skills, namely, using the IBM SPSS Statistics program. Students should be able to use a series of intermediate and advanced descriptive and inferential statistical procedures (comparison of means, measures of association and linear regression), using parametric and non-parametric tests, to analyze experimental and correlational designs. This unit emphasizes the acquisition of effective analysis skills, within the scope of the general linear model, of the variability naturally existing in psychosocial data. 

Work Placement(s)

No

Syllabus

A - Theoretical concepts

1. Introduction to Statistics: Basic concepts, data types, uses and abuses of Statistics, stages of a statistical study, planning of experiments.

2. Univariate Descriptive Statistics: Think in statistical terms, correlation and cause-effect relationship, organization and presentation of data, central location indicators; dispersion indicators; coefficient of variation; asymmetry and flattening indicators (kurtosis).

3. Normal Distribution: The normal curve; central limit theorem; distribution of the sample mean.

4. Inferential Statistics: Fundamental concepts; mistakes in decision making; confidence intervals and hypothesis testing; inference on the average value; inference about difference in mean values of two populations; the chi-square test for adherence and contingency.

5. Non-parametric tests for two samples: independent and related plans.

B - Practices / Laboratories

1. Use of the IBM SPSS Statistics menus to implement the different techniques.

Head Lecturer(s)

José Manuel Pacheco Miguel

Assessment Methods

Assessment
Frequency: 100.0%

Bibliography

Aliaga, M. & Gunderson, B. (2006). Interactive Statistics (3rd Ed.).  Prentice Hall.

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

Field, A. (2017). Discovering Statistics Using SPSS (5th 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.

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.