Statiscs Elements

Code:

M1022

Acronym:

M1022

Level:

100

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2019/2020 - 1S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:BQ	83	Official Study Plan	2	-	3	28	81

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.
It is also expected that the student acquires familiarity with different software used in statistical analysis, such as R, Excel and SPSS, in the framework of problems solving.

Learning outcomes and competences

It is intended that the student will:

. 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. 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. 

3. 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. 

4. 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

Óscar Felgueiras; Apontamentos disponibilizados pelo docente

Complementary Bibliography

000101723. ISBN: 978-84-481-6099-2
000089262. ISBN: 0-471-45232-7
Fernanda Figueiredo, et al.; Estatística Descritiva e Probabilidades, Escolar Editora, 2009. ISBN: 9789725922491

Teaching methods and learning activities

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

Software

Excel
SPSS
R

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	40,00
Teste	60,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	53,00
Frequência das aulas	28,00
Total:	81,00

Eligibility for exams

Attendance is not mandatory.

Calculation formula of final grade

There are 5 mini-tests during the semester and the Test component grade is obtained by considering the sum of the 2 best mini-test scores among the first 4 (each worth 6 out of 20) with the score obtained in the 5th mini-test (worth 8 out of 20). Attending the 5th mini-test is mandatory in order to obtain a valid score in this component.

Exam exemption:

In case the student decides not to attend the first season exam, the test component score rounded to the nearest unit serves as the final grade in the course, as long as a minimum score of 2.0 (out of 8) has been obtained in the 5th mini-test. However, in this situation, the final grade will be limited to a maximum of 16, ie, grades higher than 16 can only be reached by doing the exam. 


First exam season:

A minimum grade of 6.0 (out of 20) in the test is required in order to attend the first exam.

Final grade:

The exam is composed of two parts (E and T). The grade obtained in the second part (T) replaces the Test component grade in case it is higher. The final grade is given by the following formula:
0.4 x E + 0.6 x T