Probability and Statistics (2500014) – Course 2025/26 PDF
Contents
Scale, support and data transformation. Location and dispersion measures Graphic representations. Sample distribution. Multivariate data. Covariance and linear correlation. Minimum square line fit. Trends
Dedication
4h Large group + 2h Laboratory classes + 8h 23m Self StudyDefinition and properties of probability Total probability theorem and Bayes theorem. Probability calculation
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4h Large group + 2h Medium group + 8h 23m Self StudyRandom variable General discrete models. Commonly used discrete models. Continuous models. Frequently used continuous models. Normal distribution. LogNormal and logitNormal distributions Simple transformations of random variables. Model applications
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8h Large group + 3h Medium group + 15h 24m Self StudyElementary simulation methods. Simulation and representation of samples.de mostres. Basic MonteCarlo method.
Dedication
2h Laboratory classes + 2h 48m Self StudyMultivariate probabilistic models Multivariate normal distribution and Central limit theorem
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3h Large group + 4h 11m Self StudyDedication
10h Laboratory classes + 14h Self StudyStatistics. Estimators. Method of moments Likelihood of a sample. Maximum likelihood method. Properties of estimators Applications of point parameter estimation. Central limit theorem. Distributions of usual statistics.
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3h Large group + 2h Medium group + 2h Laboratory classes + 9h 48m Self StudyHypothesis tests Contrasts in normal context Contrasts in Normal context Simulated contrasts. Other contrast statistics
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3h Large group + 3h Medium group + 2h Laboratory classes + 11h 12m Self StudyLinear regression least squares model. Hypotheses and assessment of the model More Linear Model. ANOVA
Dedication
7h Laboratory classes + 9h 48m Self Study