Class Probabilities and Statistics

The Probability and Statistics course aims to provide the student with fundamental concepts of of probability theory and techniques of descriptive statistics and statistical inference, essential for the study of Engineering.  

Not applicable

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. Confidance intervals and hypothesis tests for a proportion. 

  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. Each student is required to attend at least 75% of the practical classes in order to have the opportunity to make continuous assessment. Otherwise, they will only be able to perform the evaluation in the appeal period. Student workers are not covered by this rule.   The assessment includes a continuous component, which involves completing three  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.

Murteira, B. (2012), Probabilidades e Estatística, vols. I e II MacGraw-Hill. Murteira, B. (2007), Introdução à Estatística, MacGraw-Hill. Morais, M.C. (2020). Probabilidades e Estatística: Teoria, Exemplos & Exercícios. IST Press (Coleção Ensino da Ciência e da Tecnologia). Ross, S. M. (2014). Introduction to Probability and Statistics for Engineers and Scientists. 5th ed, Academic Press.