Experimental Design and Modelling

1
Experimental Design and Modelling

• Harry R. Erwin, PhD
• School of Computing and Technology
• University of Sunderland

2
Resources

• Rowntree, D. (1981) Statistics Without Tears.
  Harmondsworth Penguin.
• Hinton, P.R. (1995) Statistics Explained. London
  Routledge.
• Hatch, E.M. and Farhady, H. (1982) Research
  Design And Statistics For Applied Linguistics.
  Rowley Mass. Newbury House.
• Crawley, MJ (2005) Statistics An Introduction
  Using R. Wiley.
• Gonick, L., and Woollcott Smith (1993) A Cartoon
  Guide to Statistics. HarperResource (for fun).

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Module Outline

• Introduction
• Using R
• Data analysis (the gathering, display, and
  summary of data)
• Probability (the laws of chance)
• Statistical inference (the drawing of conclusions
  from specific data knowing probability)
• Experimental design and modeling (putting it all
  together)

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Lecture Outline

• Experimental Design
• The process of defining how to collect data that
  will allow you to falsify a hypothesis.
• Modelling
• The process of defining how the data youve
  collected might be best explained.
• Involves regression, ANOVA, and ANCOVA

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Experimental Design
6
Modelling

• This is the process of defining a minimal model
  for the data.

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Regression Analysis

• Handles continuous data.

8
ANOVA

• Handles categorical data
• Why does it involve variance?

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ANCOVA

• A mixture of regression and ANOVA.

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Summary

• Theres a lot more to statistics.
• Crawley is a good reference if youre planning to
  do a statistical analysis.
• If your analysis has any complexity, consult a
  working statistician. I am an experimental
  scientist, not a working statistician, but I do
  run a weekly statistical surgery. This semester,
  it meets in DGIC 109 from 2-3 pm on Wednesdays.
• Good Luck!