Probability and Statistics

This curricular unit uses knowledge from Applied Mathematics I and II or Mathematical Analysis I and II.

According to the curricular plan, classes are theoretical – practical. In the theoretical component, theoretical concepts associated with the topics mentioned in the syllabus are presented, sometimes with the help of slides written by the teacher. The practical component consists of solving practical problems in the area of management sciences.

The support materials are available on the Nonio platform.

Statistics is a fundamental science in the analysis of situations that include scenarios of uncertainty, having many applications in the management area.

In this course unit it is intended that students understand the main concepts of descriptive statistics, more specifically, that they know how to analyze a single statistical variable and also relationships and associations that may exist between variables and that they know the probabilistic models that are the basis of statistical inference.

It is also intended that students are able to apply the statistical techniques studied in solving practical problems, and know how to interpret their results in a critical way.

 1 – Descriptive statistics

    1.1 – Introduction

   1.2 – Qualitative data and quantitative data (discrete and continuous)

   1.3 – Describing data: tables and graphs

   1.4 – Measures of location

   1.5 – Measures of dispersion

   1.6 – Measures of shape

   1.7 – Gini Coefficient and Lorenz Curve

2 – Simple regression analysis

   2.1 – Introduction

   2.2 – Correlation analysis

   2.3 – Simple regression model

   2.4 – Coefficient of determination

   2.5 – Prediction

3 – Introduction to index numbers

4 – Introduction to probability theory

    4.1– Fundamental concepts

   4.2 – Concepts of probability

   4.3 – Axiomatic definition of probability

   4.4 – Conditional probability and independent events 

5 – Random variables

   5.1– Introduction

   5.2 – Distribution function

   5.3 – Discrete random variables: probability functions

   5.4 – Continuous random variables: probability density functions

   5.5 – Expected values and moments

6 – Usual probability distributions 

   6.1 – Discrete probability distributions

   6.2 – Continuous probability distributions

NAO

Murteira, B., Ribeiro, C.S., Silva, J.A. e Pimenta, C. (2010). Introdução à Estatística. Escolar Editora.

Murteira, Bento J.F. (1993). Análise Exploratória de Dados – Estatística Descritiva. McGraw-Hill.

Curto, J.D. (2016). Estatística, muitas aplicações em Excel e poucas fórmulas. 1ª ed. Guide – Artes Gráficas.

Lisboa, J.V., Augusto, M.G. e Ferreira, P.L. (2012). Estatística Aplicada à Gestão. Vida Económica.

Chaves, C., Maciel, E., Guimarães, P. e Ribeiro, J.C. (2000). Instrumentos estatísticos de apoio à economia. McGraw-Hill.

Newbold, P., Carlson, W., Thorne, B. (2012). Statistics for Business and Economics, 8th Edition Pearson.

Pedrosa, A.C. e Gama, S.M. (2004). Introdução computacional à Probabilidade e Estatística. Porto Editora.

Paulino, C., Branco, J. (2005). Exercícios de Probabilidades e Estatística. Escolar Editora.