-
Presentation
Presentation
This subject is devoted to fundamental concepts in the theory of probability, statistics and statistical inference
-
Class from course
Class from course
-
Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 6
-
Year | Nature | Language
Year | Nature | Language
2 | Mandatory | Português
-
Code
Code
ULHT2531-15
-
Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
-
Professional Internship
Professional Internship
Não
-
Syllabus
Syllabus
1. . Descriptive Statistics
Types of data: integers, continuous, categorical, arrays, matrices
Frequency tables Measures of central tendency and variability
Visualization
2. Linear Regression
Independent vs. dependent variables. Scatter plots
Covariance and Pearson coefficient Regression line
Residuals, least squares method Calculating the estimate for the response given a certain value for the independent variable
3. Probability
Random experiment. Sample space. Event. Operations between events
Properties of the probability function. Probability of the union of events Law of total probability Bayes' theorem
Conditional probability. Independent events
4. Statistical Inference
Sample and random sample
Estimator and estimate for a proportion
Hypothesis test for a proportion
-
Objectives
Objectives
This subject aims to show that
LG1: probability is as an essential measure function in science.
LG2: statistics enables us to collect data, analyse data, establish hypothesis on data and test these hypothesis. Hence, both probability and statistics lead us to knowledge in science and engineering
-
Teaching methodologies and assessment
Teaching methodologies and assessment
- In class, the ideas underlying the curriculum of this course are discussed, and multiple examples and application exercises are analyzed.
- For each topic in this course, a set of application exercises is presented. Students are encouraged to solve these exercises and to raise any doubts they may have.
- All supporting materials and relevant information will be shared with students through Moodle.
- The assessment includes a continuous component, which involves completing three 40-minute tests and a final exam (Final Exam or Make-up). The average of the three tests is denoted as A, and the Exam Grade is denoted as B.
- If A > 9.5, the student is approved for the course and can take the exam to improve the grade. In this case, the Final Grade = max(A, B).
- If A < 9.5, the student is not approved for the course and must take the exam to obtain approval.
- Students who achieve a final grade of at least 10 points are considered approved.
-
References
References
- Morais, M. C. (2020): Probabilidades e Estatística: Teoria, Exemplos e Exercícios, IST Press (Coleção Ensino da Ciência e da Tecnologia)
- Murteira, B., Ribeiro, C.S., Andrade e Silva, J., e Pimenta C. (2010): Introdução à Estatística, Escolar Editora
- Murteira, B. (1993): Análise Exploratória de Dados - Estatística Descritiva, McGraw-Hill
-
Office Hours
Office Hours
-
Mobility
Mobility
No