Statistical modelling in R


Statistical modelling in R

Training description

On this training you will learn how to build statistical models in R. This training covers all aspects of the process of creating various types of models. You will learn how to verify model assumptions, select proper variables, build model in R, verify model quality and interpret the results.

Duration: 2 days 8 hours each (including an hour lunch break)

Requirements: knowledge of R programming language at an intermediate level which can be acquired during our training “Introduction to R”.

Training agenda

Part one: Foundations

  • Verifying the type and distribution of a variable
  • Analysing the correlation between variables
  • How to deal with missing values
  • What is an outlier and how deal with it

Part two: Linear regression

  • Model assumptions
  • Variable selection
  • Creating the model
  • Verifying model quality
  • Interpreting the results
  • Using the model to predict values for new observations
  • Including interactions in your model

Part three: Generalised linear models (GLM)

  • Logistic regression
  • Poisson regression
  • Modelling with the Tweedie Distribution

Part four: Generalized Additive Models (GAM)

  • Building and interpreting an additive model

Contact us about closed training

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