Statistical Analysis

Courses

*Degree in Management*
Statistical Analysis

Courses *Degree in Management*

Cod: 21008

Department: DCET

Department: DCET

ECTS: 6

Scientific area: Mathematics

Scientific area: Mathematics

Total working hours: 156

Total contact time: 26

Total contact time: 26

In this course we study the basic concepts of random variables, distribution laws for discrete and continuous variables, and classical statistical inference, with a view to applications in management.

Probability distributions

Statistical Inference

Hypothesis Testing

Statistical Inference

Hypothesis Testing

At the end of this course, students should be able to define and implement the most appropriate probability models for problems that are proposed. Similarly, they should be able to identify and use the classical methods of statistical inference, including methods of estimating from sample data unknown parameters of populations. Are studied parametric and nonparametric tests for two or more (brief reference) samples and tests of association. The studied methods could be used as a tool for decision support in management problems.

- The usefulness of statistics in various areas, particularly in management and economics.

Distinction between Descriptive Statistics and Statistical Inference.

Review of the Fundamentals of Probability Theory. Function of Probability / Density and Distribution Function of discrete and continuous random variables.

Distribution laws. Discrete variables: Bernoulli, Binomial, Poisson, Hypergeometric, Geometric. Continuous variables: Uniform, Normal, Exponential, Chi-square and Student t. Approximations of sums of random variables. Central Limit Theorem.

Estimation of parameters. Confidence Intervals. Parametric and nonparametric tests for one, two and k populations (t tests), Reference to ANOVA and nonparametric alternatives). Chi-square test.

Mandatory Reading

Reis, Elizabeth, Melo P., Andrade R., Calapez, T. Estatística Aplicada, Volumes. I e II, Edições Sílabo

Alternativas e bibliografia complementar:

Marques A. Gama, Sílvio; Pedrosa, António C.. Introdução Computacional à Probabilidade e Estatística (2007), Porto Editora

Fonseca, J., Torres, D., (2000) Exercícios de Estatística, Vol. I & II, Edições Sílabo.

Murteira, B. J., Ribeiro, C. S., Andrade & Silva, J. E, Pimenta, C. (2002), Introdução à Estatística, McGraw-Hill.

Reis, Elizabeth, Melo P., Andrade R., Calapez, T. Estatística Aplicada - Exercícios, Vol. I e II, Edições Sílabo.

Reis, Elizabeth, Melo P., Andrade R., Calapez, T. Estatística Aplicada, Volumes. I e II, Edições Sílabo

Alternativas e bibliografia complementar:

Marques A. Gama, Sílvio; Pedrosa, António C.. Introdução Computacional à Probabilidade e Estatística (2007), Porto Editora

Fonseca, J., Torres, D., (2000) Exercícios de Estatística, Vol. I & II, Edições Sílabo.

Murteira, B. J., Ribeiro, C. S., Andrade & Silva, J. E, Pimenta, C. (2002), Introdução à Estatística, McGraw-Hill.

Reis, Elizabeth, Melo P., Andrade R., Calapez, T. Estatística Aplicada - Exercícios, Vol. I e II, Edições Sílabo.

E-learning

It is recommended that students have previously attended UC 21068 Introduction to Applied Statistics.