Statistics

Code:

EM0020

Acronym:

E

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2007/2008 - 2S

Active?	Yes
Responsible unit:	Industrial Management and Engineering Section
Course/CS Responsible:	Master in Mechanical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
LEM	1	Plano de estudos de transição para 2006/07	2	6	6	56	160
MIEM	195	Syllabus since 2006/2007	2	-	6	56	160
		Plano de estudos de transição para 2006/07	2	-	6	56	160

Teaching language

Portuguese

Objectives

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.

SPECIFIC AIMS:
The aim of this discipline is to assure that the students of the "Mestrado Integrado em Engenharia Mecânica" acquire an integrated knowledge of the main Statistical Concepts

PREVIOUS KNOWLEDGE
No previous knowledge is required.

PERCENTUAL DISTRIBUTION
100 % scientific

LEARNING OUTCOMES:
At the end of the semester, the students should:
1. Be aware of the fundamental statistical techniques;
2. Be able to have a critical perspective of the results obtained through the use of the major statistical analysis methods.

Program

1. Introduction to Statistics: Scope and method;
2. Descriptive statistics: Description of univariate and bivariate samples of quantitative or qualitative data.
3. Basic probability theory. Variables and probability distributions;
4. Distributions of discrete and continuous variables. Distribution parameters. Transformed variables. Joint Distribution of two variables: Joint, marginal and conditional distributions. Independent variables. Covariance and correlation. Distribution of functions of two variables.
5. Probability distributions of discrete random variables: the Binomial distribution, the Hypergeometric distribution and the Poisson distribution.
6. Probability distributions of continuous random variables: the Uniform distribution, the Negative exponential distribution, and the Normal distribution. The t distribution, the Chi-square distribution and the F distribution;
7. Random sampling and sampling distributions: Distribution of the sample mean. The Central limit theorem. Generation of discrete random variables;
8. Statistical inference: confidence intervals;
9. Statistical inference: hypothesis tests. The control chart as a practical application of the hypothesis tests.

Mandatory literature

Guimarães, Rui Manuel Campos; Estatística. ISBN: 978-84-481-5589-6
Wonnacott, Thomas H.; Introdução à estatística. ISBN: 85-216-0039-9

Teaching methods and learning activities

Lectures: where the main concepts of Statistics are taught.
Tutorial Classes: where the students solve and discuss practical exercises.

Software

Microsoft Excel.

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Subject Classes	Participação presencial	56,00
Problem Solving	Teste	35,00
Tests ans Exams	Exame	6,00
Use of Excel or SPSS to solve an assignement	Exame	30,00
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Study	Estudo autónomo	35
	Total:	35,00

Eligibility for exams

Minimum attendance to the practical classes, in accordance with the Evaluation Standards of FEUP.

Calculation formula of final grade

The final mark depends on:
Final Mark = (0.30* 1º Test + 0.30* 2º Test + 0.40* 3º Test).
In case the student reaches a final classification of seven points (out of 20), he can attend a final exam in order to substitute the mark of the lower test.

Special assessment (TE, DA, ...)

In accordance with the Evaluation Standards of FEUP.

Classification improvement

In accordance with the Evaluation Standards of FEUP.