Statistics I

Code:

EIG0015

Acronym:

E I

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2013/2014 - 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	89	Syllabus since 2006/2007	2	-	6	56	162

Teaching language

Portuguese

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 Statistics II, 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: (I) identifying the concepts of this course unit in a structured way; (II) using tools of descriptive statistics in the analysis of data samples; (III) solving common problems, which involve elementary probability theory, random variables, probability distributions and point and interval estimation; (IV) 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.

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

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

Software

SOFA
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	65,00
Teste	20,00
Trabalho escrito	15,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de relatório/dissertação/tese	10,00
Estudo autónomo	66,00
Frequência das aulas	56,00
Trabalho laboratorial	30,00
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 = 0.20 FA + 0.15 TG + 0.65 EF

FA - Quizzes:
- 6 quizzes (pratical classes);
- the quizzes mark (FA) is obtained by the average of the best 4 marks achieved by each student.

TG - Teamwork assignments:
- 2 small size teamwork assignments (TG1 e TG2).

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.