1. Socio-cultural Context of research

2. Research takes place in a particular time in history and in a particular culture Can not avoid this problem of the research context. –Can influences topics of research Problem when it is not recognised –e.g lack of cross-cultural equivalence –Can prevent research being done e.g. Scarr (1988) –Can influence interpretation of data Berger and Tedeschi (1969) phenomenon which we are studying are constantly changing

3. Ethics Culturally determined Nuremberg Code Ethical guidelines for research –APS http://www.psychsociety.com.au/about/code_of_ethics_2001.pdf –NHMRC http://www.health.gov.au/nhmrc/publications/humans/preamble.htm

4. Tricky Issues relating to ethics Informed consent Deception Social value

5. Revision Scales of measurement Measures of central tendency and variability Shape of distribution Standard scores and normal distribution Hypothesis testing (Do not need to cover probability in detail) Significance - comparing calculated statistic to critical value vs probability to alpha Power and effect size. Difference between parametric and non parametric

6. NominalOrdinalInterval SymetricalSkewed Central Tendency Variability

7. NominalOrdinalInterval SymetricalSkewed Central Tendency Mode Variability

8. NominalOrdinalInterval SymetricalSkewed Central Tendency ModeMedian Variability

9. NominalOrdinalInterval SymetricalSkewed Central Tendency ModeMedian VariabilityInterquartile range

10. NominalOrdinalInterval SymetricalSkewed Central Tendency ModeMedianMean VariabilityInterquartile range

11. NominalOrdinalInterval SymetricalSkewed Central Tendency ModeMedianMeanMedian VariabilityInterquartile range

12. NominalOrdinalInterval SymetricalSkewed Central Tendency ModeMedianMeanMedian VariabilityInterquartile rangeStandard Deviation

13. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two Test

14. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square

15. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square Wilcoxon Rank-Sum

16. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square Wilcoxon Rank- Sum Wilcoxon matched pair signed rank

17. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square Wilcoxon Rank- Sum Wilcoxon matched pair signed rank Indep. t-test

18. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square Wilcoxon Rank- Sum Wilcoxon matched pair signed rank Indep. t-test Oneway ANOVA

19. Hypothesis Testing Scale of Measurement NominalOrdinalInterval DesignBetweenWithinBetweenWithinBetweenWithin Number of Groups two or more Twotwo More than two twoMore than two TestChi- square Wilcoxon Rank- Sum Wilcoxon matched pair signed rank Indep. t-test Oneway ANOVA Dep. t-test

20. MEASURES OF ASSOCIATION

21. Both variables Interval –Pearson Product Moment Correlation One or both variables Ordinal –Spearman Rank Order Correlation

22. Examination 45 MCQ -.33 weighting 15 Short answer questions -.67 weighting –Must answer all questions, ie no choice May take in to examination one A4 page of original handwritten notes

23. Types of questions Identify the appropriate statistical test to use. Requires knowledge of measurement and statistical tests cf assignment. Definite question. Identify threats to validity. Definite question. Interpret SPSS printouts. Definite question. Need to know basic formulas - enhances understanding of concepts. For example what is variance, F ratio etc. But will be no major calculations eg will not be given a set of data and asked to calculate t. Explain the underlying process of hypothesis testing. What is a sampling distribution. What is a sampling distribution and how is it used. What is sampling error. Explain why power is important. Explain or identify Type 1 and Type II errors Questions based on the tutorials. eg In ANOVA, what happens when you add a constant to the scores of one group. Ethical issues in conducting research