Statistical Methods

Objectives

1. Compreender os fundamentos dos métodos utilizados em Estatística e dos seus pressupostos;

2. Aplicar os métodos adequados aos dados disponíveis, reconhecer e interpretar os resultados e tomar decisões apoiadas nesse conhecimento;

3. Dominar a problemática existente em torno do estudo das propriedades de uma população a partir do escrutínio de uma ou mais amostras dessa população;

4. Adquirir competências relativas à utilização de aplicações informáticas, tais como o SPSS ou o Excel, úteis no domínio da análise de dados.

Program

1. Descriptive Statistics: Frequency distributions. Measures of central tendency, dispersion, skewness and kurtosis. Quantiles. Graphics. Pearson product moment correlation and Spearman rank order correlation coefficient.

2. Introduction to Probability Theory and Statistical Inference: Important Concepts. One-sample t-test. Independent two-sample t-test. Dependent t-test for paired samples. Chi-Square test for single-variable experiments. Chi-square test of independence. Mann-Whitney U test. Wilcoxon signed ranks test.

3. Analysis of Variance (ANOVA), one-way and factorial, and Analysis of Covariance (ANCOVA).

4. Multivariate Analysis of variance (MANOVA),  one-way and factorial.

5. Principal Component Analysis.

6. Cluster Analysis.

7. Regression Analysis: Linear Regression (Simple and Multiple). Linearization of nonlinear models. Logistic regression.

8. Time Series Analysis.

Teaching Methodologies

The classroom sessions include a first part of theoretical exposition and a second one for problem-solving tasks and exercises of worksheets. The aim is to encourage the learning based on experience. Students use their laptops in the classroom and work with applications like Excel and IBM SPSS Statistics in the resolution of the exercises.

The teacher accompanies the students in solving exercises of worksheets, encouraging the discussion of methodologies and results obtained with the use of SPSS. Outside of classes, students should read more about the methods studied and complete the resolution of the worksheets. Students are encouraged to use the Internet to conduct research on the topics, and to ask questions by e-mail: aurea.st.sousa@uac.pt. 

Bibliography

Chatfield, C. (2000). Time-Series Forecasting. Chapman & Hall / CRC. ISBN: 1-58488-063-5 (UAç 103584 SD 519.24 C437t).

Evans, J. R.R., & Olson, D. L. (2002). Statistics, Data Analysis and Decision Modeling. Prentice Hall. ISBN: 978- 0130783837 (UAç 105618 SD 519.2).

Everitt, B. S., & Dunn, G. (2001). Applied Multivariate Data Analysis. Edward Arnold. ISBN: 0340741228 (BibUAç 519.23 E94a).

Guimarães, R. C., & Cabral, J. S. (1997). Estatística. McGraw-Hill. ISBN: 972-8298-45-5 (BibUAçSD 519.2 G98es 97049E1).

Johnson, R. A., & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis. Prentice Hall. ISBN: 0-13- 092553-5 (BibUAç EG 519.23 J65ap - 102963).

Newbold, P., Carlson, W. L., & Thorne, B. (2010). Statistics for Business and Economics; 7ª Edição, Pearson Prentice Hall. ISBN -13: 9780135072486.

Tabachnick, B. G., & Fidell, L. S. (2001). Using Multivariate Statistics. Allyn & Bacon. ISBN: 0-321-05677-9 (BibUAçSD 519.23 T111u 103841).