Regression
Goals:
Building models that allow phenomena to be related to each other, choosing the appropriate model and interpreting the results.
Techniques presented:
Main statistical techniques for the analysis of multidimensional phenomena (linear regression, generalized linear models, non
linear)
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Tutorials:
There are exercises for each of the topics covered.
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Prerequisites:
Attending the TSC course or having knowledge of the topics it contains is preparatory.
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Subjects:
Forecasting a quantitative phenomenon
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Simple linear regression
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The regression line
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The assumptions of the regression model
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Multiple linear regression
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Diagnostic analysis (Residuals, Influences, Leverage, Collinearity)
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The generalized linear model
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The analysis of variance
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Multivariate analysis of variance and repeated measures
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The mixed affect models
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Introduction to nonlinear models
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The polynomial regression
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The neural networks
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Prediction of a qualitative phenomenon
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Logistic regression