1. Levels of measurement

2. DesignType of data Nominalordinalinterval Repeated measures Sign testWilcoxon sign test Related t test Matched pairs Sign testWilcoxon sign test Related t test Independent measures Chi squared Mann- Whitney ‘U’ Unrelated t test CorrelationChi squared Spearman rho Pearson moment

3. Nominal (categorical data) Where numbers usually refer to people in categories It is crude and unsophisticated Ppts don’t get a score – they are the scores!

4. Type of sport preferred MalesFemales Competitive3517 Non- competitive 1533 The number of males and females who prefer competitive and non-competitive sports

5. Task Collect some nominal (categorical) data from this class Display your results in the form of a table

6. Ordinal data Where the score obtained are on a numerical scale and can be put in order from highest to lowest However, the units of measurement are not of equal, definable size Usually based on opinion therefore tend to be subjective rather than objective

7. e.g. on a scale of 1-10 (1= not very…10=very)…. How happy would you rate yourself at the moment? How well do you think your exams went? How disappointed are you now that England are out of the world cup?

8. How could these variables be more precisely measured? Happiness Estimated exam performance Disappointment

9. Interval data Data is on a numerical scale with units of equal, definable size E.g. reaction time E.g. height E.g. pulse rate (try this). Note that interval data can be converted to ordinal data, and ordinal data can be converted to nominal data

10. Do you think the following are examples of interval data Words recalled from a list IQ scores

11. Note how different measures of central tendency are used dependent upon the level of measurement used Intervalxxyes Ordinalxyesx NominalyesXX ModeMedianMean