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Modelling Real World Data

How do we represent measurements from the real world using data scientific techniques? Lovisa Sundin and Jeremy Singer discuss standard approaches.

In general, data is either numbers (numerical data) or labelled values from a limited set of possible values (categorical data).

Numerical data may be discrete (whole numbers) or continuous (real numbers, with decimal points).

As a short exercise, think of an example of numerical data and categorical data for features from the following data sets:

  1. Scotland’s 2001 census data
  2. Bicycles in the Glasgow city bike hire scheme
  3. Olympic Games athletes data

As a further thought experiment, can you see how values of these different kinds might map onto the concrete data types Jeremy introduced in an earlier video?

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Getting Started with Teaching Data Science in Schools

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