Statistics I

Code:

EIG0015

Acronym:

E I

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2007/2008 - 1S

Active?	Yes
Responsible unit:	Industrial Management and Engineering Section
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
LGEI	0	Plano de estudos de transição para 2006/07	2	6	6	56	160
			3
MIEIG	76	Plano de estudos de transiçao para 2006/07	2	-	6	56	160
			3
		Syllabus since 2006/2007	2	-	6	56	160

Teaching language

Portuguese

Objectives

It is expected that, by the end of this course, the students fully understand the basic statistical concepts, particularly those concerned with the deductive path “population-sample”. It is also expected that, by the end of Statistics I and II, the students fully understand the concepts of statistical inference and are able to use statistical methods and techniques with a high degree of autonomy.

Program

General Introduction: Populations and samples. Steps of the statistic analysis methodology. Descriptive Statistics. Probability. Conditional probability. Independence. Bayes theorem. Probability distribution. Discrete and continuous random variables. Distributions parameters. Transformation of random variables. Joint distributions of two variables. Marginal distributions. Independence. Covariance and correlation. Functions of two random variables. Distributions of discrete random variables: the Binomial, the Negative Binomial the Hypergeometric and the Poisson distributions. Distributions of continuous random variables: the Uniform, the Negative Exponential, the Normal, the Student t, the Chi-squared, and the F distributions. Random sampling and sampling distributions: Distribution of the sample mean. Central limit theorem. Generation of random variables

Mandatory literature

Guimarães, Rui Manuel Campos; Estatística. ISBN: 978-84-481-5589-6

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.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Subject Classes	Participação presencial	56,00
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Study time	Estudo autónomo	106	2007-12-18
	Total:	106,00

Eligibility for exams

It is required the attendance on, at least, 75% of the classes.

Calculation formula of final grade

The final classification is the weighted average of the results obtained on the four tests. The weighs are 0.10, 0.20, 0.30 e 0.40, respectively.

Examinations or Special Assignments

None.

Special assessment (TE, DA, ...)

The four tests are mandatory