AQA A-level psychology advanced research methods year 13
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| Sign test | For finding differences in paired/dependant samples of nominal data
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| How data is ranked for sign tests | Minus that data if the second condition from the first condition. If the answer is positive, that category is awarded a plus, if it is negative, that category is awarded a minus
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| How the sign test is calculated | The critical value is determined by the total number of signs (N) and if it is one or two tailed, the less common sign (S) is compared to the critical value. If it does not exceed the critical value then the null hypothesis is rejected and vice versa
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| 3 key questions for choosing a statistical test | What level of measurement is it? (Nominal, ordinal, or interval)
Is it testing correlation or difference? (Correlation is 2 continuous variables, correlation is multiple catagories)
What experimental design is it? (Related or unrelated)
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| Tests for nominal data (2) | Chi squared - related
Sign test - unrelated
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| Tests for ordinal data (3) | Mann Whitney - related
Wilcoxon - unrelated
Spearman’s rank - association
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| Tests for interval data (3) | Unrelated t-test - related
Related t-test - unrelated
Pearson’s R - association
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| Acronym for tests | N - Cramming Sessions
O - Make Weekends Stressful
I - Use Regular Preparation
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| Wilcoxon test | Non-parametric test of difference between 2 scores for ordinal unrelated data
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| Parametric tests | Tests that make assumptions about the population distribution from which a sample is drawn
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| Non-parametric statistics | Tests that make no assumptions about sample size or if observed data is quantitative
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| How to calculate Wilcoxon test | Minus latter data from initial data and rank differences, excluding zeros, add pluses together, minuses together, smallest of those 2 values is T (OV), the total number of values is N which is used to find critical data and compare to calculate value
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| Mann-Whitney test | A non-parametric test of difference for independent groups design using ordinal data to calculate difference between two populations
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| How to calculate Mann-Whitney test | Two calculated U values are found for each population, the smallest one is selected. The critical value is found by looking at the number of each population on the table
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| Chi squared | Used for categoric data to see if the observed data matches with expected data. Degrees of freedom are number of categories minus 1 x number of rows minus 1 and X^2 must be greater than or equal to the critical value
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| T-test | A parametric test of difference for any experimental design using interval data. Used to find the difference between two means. Comes in two forms: related t-test and unrelated t-test
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| Related vs unrelated t-test | They’re the same test with the same calculation except for how the critical value is calculated and what type of experimental design they’re used for. The value of t must be greater than or equal to the critical valye
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| Spearman’s vs Pearson’s rank | They are both used to establish correlation between 2 continuous variables except Pearson’s rank assesses linear relationship whereas Spearman’s rank can assess any type of relationship. Pearson’s rank requires degrees of freedom
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