Probability and Statistics

Code:

M271

Acronym:

M271

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2016/2017 - 1S

Active?	Yes
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Bachelor in Physics

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:AST	1	Plano de Estudos a partir de 2008	2	-	7,5	70	202,5
L:F	1	Plano de estudos a partir de 2008	2	-	7,5	70	202,5
			3
L:G	0	P.E - estudantes com 1ª matricula anterior a 09/10	3	-	7,5	70	202,5
		P.E - estudantes com 1ª matricula em 09/10	3	-	7,5	70	202,5
MI:EF	26	Plano de Estudos a partir de 2007	2	-	7,5	70	202,5

Teaching language

Portuguese

Objectives

An Introductory course in Probability and Statistics: acquisition of basic concepts of Probability and Statistics and their application to concrete situation
Particular attention is paid to the presentation and understanding of the concepts, keeping the mathematical treatment on an medium level.

Learning outcomes and competences

On completing this curricular unit it is expected that the student:

1. can understand the concepts involved in a statistical study and be aware of the various problems that arise in each particular study.
2. can identify and apply appropriate techniques of descritive statistics to organize and summarize data and interpret them;
3. dominates the probability calculus and knows to calculate probabilities associated with the phenomenon under study;
4. be able to characterize random variables/random vectors and identify the respective probability distributions;
5.  be able to make inferences on population parameters applying techniques of point and interval estimation.

Working method

Presencial

Program

1. Basic concepts in Statistics: Populations and samples; the role of randomization; observational and experiment studies; statistical variables.


2. Descriptive Statistics: fundamental concepts and tecniques for summarizing data.

3. Probability Theory: fundamental concepts, probability interpretations, independence of events and conditional probability, Bayes’ and total probability theorems.



2. Random Variables: characterization, discrete and continuous models; function of a random variable, moments; Discrete distributions:  the uniform, binomial and poisson distributions; the uniform, exponentisal, normal distributions, student's t distribution and  chi-squared distribution. Chebyshev's inequality, central limit theorem.

4. Statistical Inference: point estimation, estimators properties, maximum likelihood estimators, interval estimation.


Mandatory literature

Introdução à estatística; Murteira Bento & all. ISBN: ISBN: 972-773-116-3
Applied Statistics and Probability for Engineers, John Wiley & Sons, 2003; Douglas C. Montgomery, George C. Runger. ISBN: ISBN: 0-471-20454-4
Chance encounters; Wild Christopher J.. ISBN: ISBN: 0-471-32936-3

Teaching methods and learning activities

Software

R

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	100,00
Total:	100,00

Calculation formula of final grade

Final classification obtained by continuous assessment:
Final note = 0.4xT1 + 0.6xT2 where
T1 = the first test rating
T2 = the second test rating
The tests have a minimum score of 8 points.


Final classification obtained by examination:
Note of the final exam.




Students with a score greater than or equal to 17.5 values in the final exam must make a complementary written or oral exam in order to obtain a score greater than or equal to 18 values.

Examinations or Special Assignments