Applications of a stochastic model , Software Engineering

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Aims: The aims of this report are to enable you to explore the background, motivations, history,  development and/or applications of one of the stochastic models.   You may choose any of the models or aspects of a model. You may choose to research any aspects of its development, the researchers involved, applications, extensions, etc.

Resources:  You may reference papers, websites, or books. You should  have at least  five references.

Brief outline: Specifically, you are required to choose, describe and discuss some aspects of how a selected stochastic model developed, and how these developments were motivated by, and/or affected, applications or theoretical developments.

You could include in your report some of the following:

  • describe and discuss the background to the model - how it came about. What drove its development - practical problems, changes in thinking in another discipline? Linking a number of problems or applications?
  • consider who were involved in the developments - what did they do or develop that was of significance, and who did they work or link with?
  • consider if there was any controversy either in the statistical development itself or in its application?
  • and what impact did it have? Did it lead to further developments? How does it fit with other models, theory or applications?

The above are just suggestions that may help you find your own ideas. Your report must have an introduction and references; apart from these, you may choose to use sections according to your taste.

Criteria

The criteria for assessment can be thought of in three components:

  • evidence of thoughtful reading/exploration
  • evidence of understanding the significance, impact and motivations for theoretical developments , applications and relationships with other models, theory or disciplines
  • clear, well-structured reporting and referencing.

Do not be too ambitious, and do not think that you need to follow, understand or give details of sophisticated statistical concepts or techniques.


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