Inferential Statistics

Joy of joys, it's stats time.


Significance Tests - Intro

What are significance tests for?

  • Significance tests are used to see just how far an IV caused a DV in an experiment, as opposed to it being due to chance
  • They work on probability, with 1 = absolutely will happen, 0 = absolutely won't happen


  • Experimental - the IV affected the DV, and a significant difference was seen
  • Null - the IV had no effect on the DV, and any difference was due to chance
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Significance Tests - Levels of Significance

Which level of significance should we use?

  • <50% or <0.5 - NO
  • This would give too much margin for error, leading us to reject the null when we had really ought to accept it
  • The results were due to chance after all
  • This is called a Type 1 error
  • <1% or <0.01 - NO
  • This is too strict: we might accept the null when we should have rejected it
  • The results were due to the IV after all
  • This is called a Type 2 error
  • <5% or <0.05 - YES
  • This is ideal for social science
  • A 5% probability that it was due to chance - we can live with
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Levels of Data


  • When data is put into categories or just named
  • E.g. favourite subject at school, did you finish the race (yes/no)


  • When data is ranked
  • You can line them up but the difference between them might not be the same
  • E.g. positions in a race, strongly agree/disagree


  • Has equal measurements on a measurement scale, e.g. temperature: there is the same difference between 4 and 6 degrees as between 10 and 12 degrees
  • No true zero - zero doesn't mean nothing. 0 degrees doesn't mean no temperature and 0 on an intelligence test doesn't mean you have no intelligence


  • Has a true zero, e.g. weight and distance: 0 kgs really is no weight
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Choosing a Statistical Test

Is it nominal data?

  • Yes - use CHI-SQUARE
  • No - move on

Is it a correlation?

  • Yes - use SPEARMAN'S RHO
  • No - move on

Is it a test of difference between two sets of scores?


Which one do you use?

  • Repeated Measures - WILCOXON T
  • Independent Measures - MANN-WHITNEY U
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