Probability and Statistics

Code:

M271

Acronym:

M271

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2014/2015 - 1S

Active?	Yes
Web Page:	https://moodle.up.pt/course/view.php?id=3182
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	4	Plano de Estudos a partir de 2008	2	-	7,5	70	202,5
L:B	0	Plano de estudos a partir de 2008	3	-	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
L:M	58	Plano de estudos a partir de 2009	2	-	7,5	70	202,5
L:Q	0	Plano de estudos Oficial	3	-	7,5	70	202,5
MI:EF	28	Plano de Estudos a partir de 2007	2	-	7,5	70	202,5

Teaching language

Portuguese

Objectives

Acquisition of basic concepts of Probability and Statistics and their application to concrete situations.

Learning outcomes and competences

On completing this curricular unit it is expected that the student

a.dominates the probability calculus and  knows to calculate probabilities associated with the phenomenon under study;

b.
be able to characterize random variables and identify the respective probability distributions;

c.
can identify appropriate techniques of descritive statistics to organize and summarize data and interpret them;

d.
be able to infer population parameters from a sample of that population applying techniques of point and interval estimation.

Working method

Presencial

Program

1. 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, bidimensional random variables, function of a random variable, moments, moment-generating function, Chebyshev's inequality, Poisson process, central limit theorem and law of large numbers.



 

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

 

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


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Mandatory literature

000101723. ISBN: 978-84-481-6099-2
000068975. ISBN: 0-471-20454-4

Teaching methods and learning activities

Lectures: presentation and discussion of the subjects listed in ‘Syllabus’.

Practical classes: solving exercises previously proposed to students; hints to solve exercises not solved in class; support in clarifying theoretical and/or practical problems.

 

Evaluation Type

Evaluation with final exam

Assessment Components

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

Calculation formula of final grade

Final exam mark, if less than 17.5. 

In the case of a final exam mark higher than or equal to 17.5,  the student must perform a complementary written or oral exam in order to obtain a score greater than or equal to 18 values.
The student can be exempted from the final exam through the realization of two assessments in which he obtains an average of at least 10. 

Examinations or Special Assignments

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.

Special assessment (TE, DA, ...)

Exams under speacial conditions will consist of a written test which can be preceded by an oral eliminatory exam.

Classification improvement

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