Class Statistics II

This course unit aims to consolidate and expand students' quantitative analysis skills through the study of advanced statistical methodologies. The curriculum includes:   Introduction and application of probability distribution models Fundamentals of statistical inference and their underlying assumptions Development of the ability to recognize and apply statistical tools across diverse contexts, with emphasis on students' fields of study The course fosters critical understanding of the utility and versatility of statistical techniques, preparing students to apply them in real-world research and decision-making scenarios.

Not applicable

Probability distribuitions Probability distribuitions for discrete random variables (uniform, binomial, negative binomial, hypergeometric, Poisson). Probability distribuitions for continuous random variables (uniform, normal, exponential, t-Student, chi-square). Aproximations. Estimation Introduction to point estimation Confidence intervals for a population mean, variance and standard deviation. Confidence intervals for a population proportion. Parametric hypothesis testing Hypothesis testing for the mean of a normal population and for a proportion of binomial population. Non-parametric hypothesis testing Chi-squared goddness-of-fit test. Chi-squared independence test.

Use of free software (GeoGebra and Microsoft Excel) to simulate probability distributions (binomial, Poisson), construct confidence intervals, and perform hypothesis tests, enabling interactive visualization of distributional approximations and p-values.

Murteira, B., Ribeiro, C.S., Silva, J.A., Pimenta, C. (2015). Introdução à Estatística, Escolar Editora. Newbold, P., Carlson, W.L., Thorne, B.M. (2012). Statistics for Business and Economics, Prentice-Hall, 8ª Edição. (ISBN: 978-0132745659) Proença, I.M. (2010). Estatística, Euedito.(ISBN: 9789892021362