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Modelling and estimation
Modelling and estimation

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Following completion of this free OpenLearn course, Modelling and estimation, you should find that your skills in making sense of discrete data are improving.

You should now be able to:

  • estimate a probability given data, and calculate a probability when assumptions about the symmetry of an object or situation can be made
  • understand how probabilities of outcomes are encapsulated in the probability mass function (p.m.f.) of models for discrete data
  • understand the meaning of the term Bernoulli trial, which describes a single statistical experiment for which there are two possible outcomes, often referred to as ‘success’ or ‘failure’
  • calculate binomial probabilities
  • appreciate that the method of maximum likelihood estimation is an important way of estimating a parameter.

This free OpenLearn course is an extract from the Open University course M248 Analysing data [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] .

If you feel you are ready to move on in your study of statistics but don’t have time to study a full Open University course at this time, you might like to study the free OpenLearn courses Medical statistics and Bayesian statistics. They are adapted extracts from the Open University course M249 Practical modern statistics.

If you are interested in pure mathematics, you might like to try the free OpenLearn courses Introduction to group theory, Introduction to linear equations and matrices and Introduction to analysis.

If you are interested in applied mathematics, you might like to try the free OpenLearn courses Second-order differential equations and Dynamics.