Overall objectives:

1 - Autonomously reviewing scientific literature containing basic statistics, so as to understand important work in specialized references.
2 - Collecting, selecting, and interpreting statistical data.
3 - Using statistics to present information and to support claims.
4 - Understanding that statistics makes it possible to go beyond a particular sample, and draw conclusions about the underlying population with a quantifiable degree of confidence.
5 - Applying classical descriptive and parametric statistical analysis techniques to study a population or variable and to compare two populations or variables.
6 - Using statistical software, particularly SPSS, for exploratory data analysis, data presentation, and basic data analysis.
7 - Solving and analysing assessment problems arising from teaching and training practice.

Syllabus:

1 - Descriptive statistics: Histogram, stem-and-leaf and boxplot. Outlier fences. Location and dispersion. Symmetry and skewness. Efficiency and resistance. Scatterplot and linear association. Least squares regression line. Coefficients of correlation and determination. Transformed linear relations.
2 - Random variables: Binomial, multinomial, and Poisson. Variance and mean value. Discrete random variables. Covariance and correlation. Conditional variables and conditional mean value. The normal distribution. Central Limit Theorem.
3 - Statistical inference: Population and sample. Estimate and estimator. Distribution of the mean and the variance in normal random samples. Confidence intervals for the mean or the variance of a normal variable. Large-sample confidence interval for a proportion. Comparing means, variances or proportions from two independent samples. Comparing the means of paired samples.

Literature/Sources:

Mosteller, F., Rourke, R. E. K. , 1992 , Estatísticas Firmes: Estatísticas Não Paramétricas e Estatísticas Ordinais , Edições Salamandra
Zar, J. H. , 1999 , Biostatistical Analysis , Prentice-Hall
Aczel, A. D. , 1995 , Statistics - Concepts and Applications , Irwin
Hoaglin, D., Mosteller, F., Tukey, J. , 1992 , Análise Exploratória de Dados, Técnicas Robustas - Um Guia , Edições Salamandra
Moore, D. S., McCabe, G. P. , 2003 , Introduction to the Practice of Statistics , W. H. Freeman
Pestana, D. D., Velosa, S. F. , 2010 , Introdução à Probabilidade e à Estatística , Fundação Calouste Gulbenkian
Rao, P. V. , 1998 , Statistical Research Methods in the Life Sciences , Duxbury Press
Vincent, William J. , 2005 , Statistics in Kinesiology , Human Kinetics Books
Triola, M. F. , 2001 , Elementary Statistics , Addison-Wesley
Wackerly, D. D., Mendenhall, W., Scheaffer, R., L. , 2002 , Mathematical Statistics with Applications , Duxbury: Thomson Learning
Tenenbaum, G., Driscoll, M. P. , 2005 , Methods of Research in Sport Sciences: Quantitative and Qualitative Approaches , Oxford: Meyer & Meyer
Coelho, J. P., Cunha, L. M., Martins, I. L. , 2008 , Inferência Estatística com Utilização do SPSS e G*Power , Edições Sílabo
Howell, D. C. , 2010 , Statistical Methods for Psychology , Wadsworth Cengage Learning
Pereira, A. , 2006 , Guia Prático de Utilização do SPSS: Análise de Dados para Ciências Sociais e Psicologia , Edições Sílabo

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
Course contents are presented in theoretical sessions, theoretical and practical sessions (solving exercises with calculator and statistical tables), and laboratorial practice sessions (solving exercises on the computer). Learning is assessed by two tests (each of them with the same weight on the final grade), to be solved with calculator and tables or on the computer. An additional element of continuous evaluation, which consists of individual problem solving during the practical or theoretico-practical classes, may contribute up to 2 points to the final grade. This continuous evaluation is optional for each student and shall only take place when expressly stated by the teacher at the start of the semester.