Statistical Methods

Code:

M2015

Acronym:

M2015

Level:

200

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2017/2018 - 1S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	0	Official Study Plan	3	-	6	56	162
L:F	0	Official Study Plan	2	-	6	56	162
L:G	4	study plan from 2017/18	2	-	6	56	162
			3
L:Q	42	study plan from 2016/17	2	-	6	56	162
			3

Teaching language

Suitable for English-speaking students

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 elementary level.

 

Learning outcomes and competences

On completing this curricular unit it is expected that the student:can understand the concepts involved in a statistical study and be aware of the various problems that arise in each particular study.

1. can identify and apply appropriate techniques of descritive statistics to organize and summarize data and interpret them;
2. dominates the probability calculus and knows to calculate probabilities associated with the phenomenon under study;
3. be able to characterize random variables and identify the respective probability distributions;
4. be able to make inferences on population parameters applying techniques of point and interval estimation.
5. be able to understand the general procedures for applying a hypothesis test.

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.

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

5. Statistical Inference: point estimation,  interval estimation,hypothesis testing.

 

Mandatory literature

Montgomery Douglas C.; Applied statistics and probability for engineers. ISBN: 0-471-17027-5
Wild Christopher J.; Chance encounters. ISBN: 0-471-32936-3
Murteira Bento; Introdução à estatística. ISBN: 972-773-116-3
Samuels Myra L.; Statistics for the life sciences. ISBN: 978-0-13-122811-5 0-13-122811-0

Teaching methods and learning activities

Theoretical lectures with exposition of the course contents.

Practical classes for solving exercises related to each theorietical topic. Support in clarifying theoretical and/or practical problems.

Software

R (opcional)

Evaluation Type

Evaluation with final exam

Assessment Components

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

Calculation formula of final grade

Final classification obtained by two tests:

Final note = 0.4xT1 + 0.6xT2 where

T1 = the first test rating

T2 = the second test rating

The tests have a minimum score of 7 points. 

Final classification obtained by examination:

Note of the final exam.

 Students will have approval to discipline the final grade (obtained in tests or examination) is greater than or equal to 10.

 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

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