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Statistics I

Code: EIG0015     Acronym: E I

Keywords
Classification Keyword
OFICIAL Mathematics

Instance: 2015/2016 - 1S

Active? Yes
Responsible unit: Department of Industrial Engineering and Management
Course/CS Responsible: Master in Engineering and Industrial Management

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MIEIG 99 Syllabus since 2006/2007 2 - 6 56 162
Mais informaçõesLast updated on 2015-07-31.

Fields changed: Objectives, Resultados de aprendizagem e competências, Métodos de ensino e atividades de aprendizagem, Fórmula de cálculo da classificação final, Programa, Lingua de trabalho, Componentes de Avaliação e Ocupação, Métodos de ensino e atividades de aprendizagem, Fórmula de cálculo da classificação final, Programa, Lingua de trabalho, Componentes de Avaliação e Ocupação

Teaching language

Suitable for English-speaking students

Objectives

This course unit aims to acquaint students with underlying knowledge on Descriptive Statistics, Probability Theory, Probability Distributions, Random Sampling, Sampling Distribution and Point and Interval Estimates. Later on, when attending to the course unit Multivariate Statistics, students will be asked to recall this knowledge in order to learn statistics techniques, which will have an important application in their future career.

Learning outcomes and competences

At the end of the semester, students should be capable of:

  • identifying the concepts of this course unit in a structured way;
  • using tools of descriptive statistics in the analysis of data samples;
  • solving common problems, which involve elementary probability theory, random variables, probability distributions, point and interval estimation, and statistical hypothesis testing (parametric and nonparametric);
  • using spreadsheets to solve the above mentioned problems.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Basic spreadsheets skills.

Program


  1. Introduction to Statistics: Scope and method.

  2. Descriptive statistics: Description of univariate and bivariate samples.

  3. Basic probability theory.

  4. Random variables and probability distributions: distributions of discrete and continuous variables, distribution parameters, transformed variables.

  5. Joint distribution of two random variables: joint, marginal and conditional distributions, independent variables, covariance and correlation, distribution of functions of two variables.

  6. Probability distributions of discrete random variables: Binomial, Hypergeometric and Poisson distributions.

  7. Probability distributions of continuous random variables: Uniform, Negative exponential, Normal, t, Chi-square and F distributions.

  8. Random sampling and sampling distributions: distribution of the sample mean, the Central limit theorem, Generation of random samples.

  9. Point estimation: estimators and estimates.

  10. Confidence intervals.

  11. Statistical hypothesis testing: Analysis of the basic procedures when running tests of hypothesis; Relationship between testing hypothesis and confidence intervals; most common tests concerning one or two populations: dispersion and location tests.

  12. Nonparametric tests: Goodness of fit, location, randomness and association tests

Mandatory literature

Guimarães, R. M. C. e J. A. Sarsfield Cabral; Estatística, Verlag Dashöfer Portugal, 2010. ISBN: 978-989-642-108-3

Complementary Bibliography

A. Miguel Gomes e José F. Oliveira; Estatística 1 - Apontamentos de Apoio às Aulas, 2012
Thomas Wonnacott, Ronald J. Wonnacott; Introdução à estatística. ISBN: 85-216-0039-9
Jay L. Devore, Kenneth N. Berk; Modern mathematical statistics with applications. ISBN: 978-1-4614-0390-6

Teaching methods and learning activities

Methods and techniques are introduced using systematically practical examples. The learning process is complemented with problem solving sessions supported by computer software and two teamwork assignments.

Software

Folha de Cálculo

keywords

Physical sciences > Mathematics > Probability theory
Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 70,00
Teste 10,00
Trabalho escrito 20,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Elaboração de relatório/dissertação/tese
Estudo autónomo 56,00
Frequência das aulas 56,00
Trabalho laboratorial 50,00
Total: 162,00

Eligibility for exams

Admission criteria set according to Article 4 of General Evaluation Rules of FEUP.

Calculation formula of final grade

The final mark (CF) will be obtained by the following formula:
CF = 0.10 FA + 0.20 TG + 0.70 EF

FA - Quizzes:
- 7 quizzes (pratical classes);
- the quizzes mark (FA) is obtained by the average of the best 5 marks achieved by each student.

TG - Teamwork assignments:
- 2 small size teamwork assignments (TG1 e TG2).
- the teamwork assignments mark (TG) is obtained by the average of the two teamwork assignments.

EF - Final Exam
- open book exam.

To pass this course, apart from a final grade no less than 10, is required a minimum grade of 7 in the final exam.

Special assessment (TE, DA, ...)

Special evaluations will be made by a final exam (closed book).

Classification improvement

Students may choose between:

- improving the components Quizzes (FA) and Final Exam (EF);

- improving only the component Final Exam (FE).

The component teamwork assignments (TG) is possible to improve.

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