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

• 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