Statistical Methods

Code:

M2015

Acronym:

M2015

Level:

200

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2016/2017 - 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	2	Official Study Plan	3	-	6	56	162
L:Q	52	study plan from 2016/17	2	-	6	56	162
			3

Teaching language

Portuguese

Objectives

To introduce the fundamental concepts, principles and methods of statistics. Emphasis is given to the understanding of the concepts and to the critical application of the methods.

Learning outcomes and competences

It is intended that the student

. Understand the fundamental concepts of probability theory and know how to calculate probabilities associated with the events being studied;

. Be able to identify the techniques of descriptive statistics appropriate to organize and summarize a data set, and how to apply them;

. Be able to characterize random variables and identify their probability distributions;

· Be able to apply adequate point and interval estimation methods to infer about the characteristics of a population based on a sample and to interpret the obtained results;

. Understand the general procedures for applying a hypothesis test.

Working method

Presencial

Program

1. Brief introduction to the objectives and methodology of statistics. 

2. Probability theory: basic concepts, operations between events, counting methods (review of the combinatorial calculus), interpretations of probability, independence of events and conditional probability, Bayes' theorem and the total probability theorem. 

3. Random variables: definition of random variable, probability function, probability density function and distribution function. Expected value, variance and their properties; two-dimensional variables. 

4. Some probability distributions: discrete distributions (binomial, geometric, hypergeometric and Poisson) and continuous (uniform, normal, exponential, chi-square and t-student); de Moivre-Laplace and the Central Limit theorems. 

5. Descriptive Statistics: definition of a statistic, types of observations and measurement scales; techniques for summarizing data (tables, graphs, measures of location and dispersion), outlier definition and the concept of correlation. 

6. Techniques of statistical inference: point estimation (main concepts and properties of the estimators), interval estimation (confidence intervals for mean, difference of means, proportions, difference of proportions, variance) and introduction to hypothesis testing. 

Mandatory literature

S. Gama; Material disponibilizado pelo docente
Pedrosa António Carvalho; Introdução computacional à probabilidade e estatística. ISBN: 972-0-06056-5
Murteira Bento; Introdução à estatística. ISBN: 978-84-481-6099-2

Teaching methods and learning activities

The practical classes are accompanied by exercise sheets relating to each of the programmatic sections.

Evaluation Type

Evaluation with final exam

Assessment Components

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

Eligibility for exams

(1) A student may be exempted from final exam by doing two tests, each quoted to ten values, realized during the semester. The student is approved provided he/she gets a grade equal or superior to 10 (= sum of the marks obtained in the tests), with a minimum of four (4) values in each test.

(2) A student who goes to the final exam gets the mark here obtained being point (1) ignored.

Calculation formula of final grade

Mark obtaines in the final exam or the arithmetic average of the test marks.

Special assessment (TE, DA, ...)

n.a.