Applied Statistics for Education

Recommended Prerequisites

No prerequisites.

Teaching Methods

Lecturing of basic contents for each subject, using audiovisual tools. Analysis of different study cases in the lab sessions with the help of statistical software (e.g. IBM SPSS Statistics). Website of the class in the LMS (Learning Management System) Nónio.

Learning Outcomes

The class “Applied Statistics for Education” is intended to enrich students with competences so that they can:

- Know the different methodologies of data analysis;

- Provide an overview of the different stages in the experimental research process preceding data analysis and which goes from the formulation of the problem to investigate to the techniques of data collection, design of the experiments, choice and operationalization of variables, and sampling methods;

- Create a greater familiarity with statistical procedures, such as simple descriptive analysis, hypothesis testing when applied to compare and to study associations between variables and populations.

- Develop analytical skills in decision-making situations in research.

Work Placement(s)

No

Syllabus

The curricular unit “Applied Statistics for Education” is intended to approach the following topics:

1. Introduction to Statistics: Basic concepts, types of data, uses and misuses of statistics, the different stages in a statistical study, design of experiments.

2. Univariate Descriptive Statistics: Thinking in terms of statistics, correlation and cause-effect relationship, organization and presentation of data, measures of central tendency and dispersion, coefficient of variation, skewness and kurtosis indices.

3. Normal distribution: the normal curve; distribution of the sample mean; the Central Limit Theorem.

4. Correlation and regression: correlation coefficient; simple linear regression.

5. Inferential Statistics: Basic concepts, errors in decision-making; confidence intervals and hypothesis testing, inference on mean; inference on differences of means of two populations, the chi-square test for independence.    

Head Lecturer(s)

Bruno Cecílio de Sousa

Assessment Methods

Final evaluation
Exam: 100.0%

Continuous evaluation
Resolution Problems: 30.0%
Frequency: 70.0%

Bibliography

Aliaga, M., & Gunderson, B. (2006). Interactive statistics (3^rd ed.). Upper Saddle River, N.J.: Pearson Prentice Hall.

Pestana, D., & Velosa, S. (2008). Introdução à probabilidade e à estatística (3ª ed.) Lisboa: Fundação Calouste Gulbenkian.

Murteira, B.  (1999) Análise exploratória de dados. Lisboa: McGraw-Hill.

Antunes, M., & Murteira, B.  (2012). Probabilidades e estatística (Vol.1 e Vol.2). Lisboa: Escolar Editora.

Carreira, A., de Sousa, B., & Pinto, G. (2002). Cálculo da probabilidade. Lisboa: Instituto Piaget.

Hoaglin, D., Mosteller, F. & Tukey, J. (1983). Análise exploratória de dados. Técnicas robustas: Um guia. Lisboa: Edições Salamandra.