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Class Fundamentos de Estatística para Ciência de Dados

  • Presentation

    Presentation

    This subject is devoted to fundamental concepts in the theory of probability, statistics and statistical inference

  • Code

    Code

    ULHT6347-25229
  • 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 that underpin the program of this Curricular Unit (CU) are discussed, and multiple examples and application exercises are analyzed.

     

    For each topic of this CU, a set of application exercises is presented. Students are encouraged to solve these exercises and to present any doubts they may have.

     

    This CU will share content and support material with another CU (Introduction to Data Science).

     

    All support material and relevant information will be shared with the students through Moodle.

     

    The evaluation includes a continuous component, which consists of three 20-minute mini-tests (whose average corresponds to 30% of the final grade) and one exam (which accounts for 70% of the final grade). Students who obtain a final grade of no less than 10 points are considered to have passed.

  • 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

     

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