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1. Descriptive and Inferential statistics What you need to knowCompulsory research methods questioncarries 35 marks so allow about 50 mins in exam 2. Descriptive stats…
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• 1. Descriptive and Inferential statistics What you need to knowCompulsory research methods questioncarries 35 marks so allow about 50 mins in exam
• 2. Descriptive stats you need to know• Measures of central tendency (mean median and mode, what they are and when to used them)• Measures of dispersion (range and standard deviation, you will not need to calculate but will need to interpret)• Graphs (bar charts and scattergrams)
• 3. Activity page 562 in blue text book
• 4. Levels of measurement• N – nominal data is frequency (tally charts)• O – ordinal data is ranked data (1st, 2nd, 3rd)• I – interval data is units of equal interval (scores, time, amount of correct answers)• R- Ratio data in same as interval but can go into negative ( temperature)
• 5. Inferential statsYou do not need to calculate stats test, however you need to understand• When to use a test• What it means• How to interpret significance levels• what the probability levels mean• Observed and critical levels• Type 1 and type 2 errors
• 6. Deciding what stats test to use• You have to ask your self 3 questions1. What level of measurement do you have (nominal, ordinal , interval/ratio data?)2. Test of difference or correlation3. Independent groups or repeated measures
• 7. Which tests do you need to know?• You only need to know 41. Chi-squared – nominal data, test of difference, independent groups2. Spearman’s rho – ordinal data, test of association, repeated measures3. Mann-Whitney – ordinal data, test of difference, independent groups4. Wilcoxon- interval data, test of difference, repeated measures
• 8. What does p < 0.05 mean? 1. the probability that1. p the results are due to chance (p)2. < 2. is less than or equal to (<)3. 0.05 3. 1 in 20 or 5% (0.05)
• 9. Probability• We can never be sure that something has caused something else to happen (that the IV has caused the changes on the DV)• Even at the most stringent levels of probability p≤0.001 (99.99%)• We never prove anything in psychology as there is not a 0% chance• We can only say the results support or contradict a hypothesis• There are two potential errors that can occur when reaching a conclusion about a hypothesis on the basis of a statistical test
• 10. Type 1 and type 2 errors• Type one error • Type two error• We might reject the null • We might retain the null hypothesis in favour of the hypothesis even though the experimental or alternative experimental or alternative hypothesis even though the hypothesis is correct results are in fact due to • Caused by probability level chance. The probability of this being too stringent? happening is given by the level of statistical significance that is given e.g. 0.05 or 5%• Caused by probability levels being too low (still a 5% probability the results occurred by chance)
• 11. Critical values when interpreting a stats result• To determine what your results mean you need to consult an appropriate table of significance• You will be provided with the relevant tables in the exam• Comparing the critical value against you own observed value lets you decide whether the null can be rejected or must be retained• In some cases the critical value must be higher and in some cases it must be lower
• 12. Comparing critical and calculated values• Chi-squared – calculated value must be greater or equal to critical value to be significant• Spearman’s rho - calculated value must be greater or equal to critical value to be significant• Mann- Whitney U - calculated value must be less than or equal to critical value to be significant• Wilcoxon signed ranks - calculated value must be less than or equal to critical value to be significant

Jul 23, 2017

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Jul 23, 2017
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