Training Course Details

Time Series Analysis with R

Time Series Analysis with R

Course Level: Intermediate

Predicting the future is a tough problem. Time series analysis makes it possible to assess whether or not predictions are possible and, if they are, build a model which can generate informed predictions for the future with realistic estimates of uncertainty. This training course will introduce participants to the packages in the Tidyverts.

The best qualification of a prophet is to have a good memory – George Savile

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Course Details

  • Course Outline
  • Learning Outcomes
  • Materials
  • Prior Knowledge

Course Outline

  • Introduction to tsibbles: Using the {tsibble} package to manipulate time series data
  • Features and Visualisation: Creating seasonal, lag and autocorrelation plots using the {feasts} package
  • STL Decomposition: De-constructing a time series into it’s seasonal and trend components
  • Introduction to forecasting: Constructing simple forecasts with the {fable} package
  • Exponential Smoothing: Creating and forecasting with ETS models
  • ARIMA models: Creating ARIMA models and forecasting

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Learning Outcomes

By the end of the day participants will be able to…

  • wrangle time series data with familiar tidy tools
  • compute time series features
  • visualise time series data in different ways
  • select an appropriate forecasting algorithm for their time series


Prior Knowledge

This course assumes basic familiarity with R and the {tidyverse}. Attending our Getting to Grips with the Tidyverse course, is more than sufficient in providing you with the prerequisite knowledge required for this course!

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