Non-Parametric Statistics

Human Resources Management and Organisational Behaviour
5 ECTS; 2º Ano, 2º Semestre, 30,0 T + 30,0 PL + 15,0 OT

Lecturer
- Maria João da Costa Antunes Inácio

Prerequisites
Not applicable.

Objectives
It is intended that students achieve in the curricular unit of non-parametric statistics the learning outcomes:
a) identify, when faced with data incompatible with parametric analysis, which statistical tests are appropriate for one sample;
b) acquire knowledge about different statistical tests to compare populations on the basis of independent or paired samples;
c) acquire knowledge about measures of non-parametric association.

Program
1. Introduction
1.1. Introduction to SPSS statistical software
1.2. Hypothesis testing
1.2.1. Null hypothesis and alternative hypothesis
1.2.2. Error type I and error type II
1.2.3. Test statistic and rejection region
1.2.4. P-value
1.3. Tests of parametric hypotheses versus tests of non-parametric hypotheses
2. Tests involving a sample
2.1. The Runs test of randomness
2.2. The binomial test
2.3. Adjustment tests
2.3.1. The Kolmogorov-Smirnov adjustment test
2.3.2. The Lilliefors Normality Test
2.3.3. The chi-square test
2.3.4. Reference to other adjustment tests
3. Non-parametric tests for two populations
3.1. Tests involving two independent samples
3.1.1. The chi-square homogeneity / independence test.
3.1.2. The Fisher's exact test for 2X2 tables
3.1.3. The Wilcoxon-Mann-Whitney test
3.1.4. The Kolmogorov-Smirnov test for two populations
3.2. Tests involving two paired samples
3.2.1. The McNemar test
3.2.2. The test of the signals
3.2.3. The Wilcoxon test

4. Nonparametric tests for more than two populations
4.1. Tests involving k independent samples
4.1.1. The chi-square test for k samples
4.1.2. The Kruskall-Wallis test
4.2. Tests involving k paired samples
4.2.1. The Friedman test
4.2.2. The Cochran Q test

5. Non-parametric association measures
5.1. Spearman's ordinal correlation coefficient
5.2. The coefficient of Cramer's C
5.3. The coefficient ró for tables 2x2
5.4. The Kendall correlation coefficient
5.5. The coefficient of agreement of Kendall
5.6. The K statistic for nominal data
5.7. Other measures of association

Evaluation Methodology
- Continuous assessment: three written midterm tests during the semester (graded 0-20) with no minimum mark required. An average mark of 10/20 in continuous assessment is required to be exempted from exam.
- Final assessment: summative exam

Bibliography
- Pereira, A. (2006). SPSS - Guia prático de utilização, Análise de dados para as Ciências Sociais e Psicologia. Lisboa: Edições Sílaba
- Siegel, S. (2006). Estatísticas Não Paramétrica Para Ciências Do Comportamento. São Paulo: Bookman

Method of interaction
Lectures and practical classes including SPSS practice exercises.

Software used in class
IBM-SPSS