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REG training

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)

Tutorials:

There are exercises for each of the topics covered.

Prerequisites: 

Attending the TSC course or having knowledge of the topics it contains is preparatory.

Subjects:

Forecasting a quantitative phenomenon

  • Simple linear regression

    • The regression line

    • The assumptions of the regression model

  • Multiple linear regression

    • Diagnostic analysis (Residuals, Influences, Leverage, Collinearity)

  • The generalized linear model

    • The analysis of variance

    • Multivariate analysis of variance and repeated measures

    • The mixed affect models

  • Introduction to nonlinear models

    • The polynomial regression

    • The neural networks

 Prediction of a qualitative phenomenon

  • Logistic regression

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