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1. Statistical Tests An idiot’s guide… by Terri (an idiot) 2. Need to know ã Level of data – Nominal – Ordinal – Interval – Ratio ã Repeat/related or…
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  • 1. Statistical Tests An idiot’s guide… by Terri (an idiot)
  • 2. Need to know • Level of data – Nominal – Ordinal – Interval – Ratio • Repeat/related or independent measures • One or two tailed hypothesis
  • 3. Levels of data: nominal • Which newspaper paper do you read regularly? • We can put these into categories.
  • 4. Levels of Data: ordinal • What grade did you get for each of your gcse’s? • These can be put in order… highest to lowest
  • 5. Levels of data: interval • How quick is your reaction time? • We can measure and compare the exact time because the intervals on the ruler are equal.
  • 6. Non Parametric Tests • Chi Square – Nominal data (categories) – Independent measures • Wilcoxon Signed Rank – Ordinal data – Repeat measures • Man Whitney U – Ordinal data – Independent measures
  • 7. Non Parametric tests • These are performed on ordinal … (or non-interval data) • They place the data into ranks before carrying out the test of probability • They are less sensitive than parametric tests
  • 8. Parametric tests • Independent t – Interval or ratio data – Independent measures • Related t – Interval or ratio data – Related measures • These are more sensitive because they perform the test for probability on the raw scores • Less likely to have type 1 or type 2 errors
  • 9. Parametric tests • Conditions for parametric testing 1.Data must be interval or ratio 2.The sample data must show normal distribution 3.Homogeneity of variance • Because they are robust these can be used even where these conditions are not fully met
  • 10. 1 tailed or 2 tailed • If the hypothesis contains a prediction the test is one tailed • If the hypothesis is non directional the test is 2 tailed • Type I error: we accept a hypothesis that is not true (our test is not tight enough) • Type II error: We reject a hypothesis that is true (our test is too tight)
  • 11. Correlations • Spearman’s Rank correlation – This is looking for a relationship between two independent sets of data – This is not used for experimental data – Looking for significant positive or negative correlations – Is used as the basis for further research because it cannot establish cause and effect
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