Statistics II

Code:

EIG0018

Acronym:

E II

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2009/2010 - 2S

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	80	Syllabus since 2006/2007	2	-	6	56	160

Teaching language

Portuguese

Objectives

1- BACKGROUND
There is no functional business area that operates today without a good understanding of Statistics. As such, Statistics plays a fundamental role in the decision making process of any engineer and should be taught in all engineering syllabus.

2- SPECIFIC AIMS
The aim of the course units Statistics I and II is to endow students of the "Mestrado Integrado em Engenharia Industrial e Gestão" with an integrated vision of the basic concepts and statistic techniques frequently applied. At the end of these course units, students should be capable of using methods of statistic analysis in an autonomous way. Statistics II is manly focused on applying statistical techniques.

3- PREVIOUS KNOWLEDGE
EIG0015: All topics.

4- PERCENTUAL DISTRIBUTION
100 % scientific.

5- LEARNING OUTCOMES:
At the end of this course unit students should be able to:
(I) define hypothesis and test them statistically;
(II) perform different types of parametric and non-parametric tests;
(III) perform analysis of variance;
(iv) perform regression analysis;
(v) use Microsoft Excel to apply the above mentioned techniques.

Program

TESTING HYPOTHESIS:
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.

NONPARAMETRIC TESTS:
Goodness of fit, location, randomness and association tests

ANALYSIS OF VARIANCE:
Models with one or two factors with fixed, variable and mixes effects

REGRESSION:
Simple and multiple linear regressions models; Stepwise linear regression; Nonlinear regression, with or without transformation of variables.


DESIGN OF EXPERIMENTS:
Introduction to the Design of Experiments; 2k Factorial Design; Fractional Factorial Design.

Mandatory literature

Guimarães, Rui Manuel Campos; Estatística. ISBN: 978-84-481-5589-6
Montgomery, Douglas C.; Design and analysis of experiments. ISBN: 0-471-31649-0

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.

Software

SPSS
R
EXCEL

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	64,00
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Conceptual learning	Estudo autónomo	96	2009-06-09
	Total:	96,00

Eligibility for exams

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

Calculation formula of final grade

Assessment will take place through two mini-tests. The Final Mark will be based on the average mark of those mini-tests.
Students have to reach a minimum average mark of 10 out of 20 and a minimum mark of 7 out of 20 in each of the mini-tests.

Examinations or Special Assignments

Not applicable

Special assessment (TE, DA, ...)

Special evaluations will be made by a final exam.

Classification improvement

At the end of the of the course unit, a final exam will take place. In such exam, students can either complete the course unit or improve their marks.