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24 Cards in this Set
- Front
- Back
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What are the three assumptions of parametric data?
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1 - The population from which the samples are drawn should be normally distributed
2 - Homogeneity of variances 3 - No extreme scores 4 - Level of data is ratio/interval |
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What is homogeneity of variance?
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That variances of the population should be equal, including an equal number of participants
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Levene’s Test for Equality of Variance - if p>.05, is there equality of variance or not?
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Yes - there is equality of variance
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Within an independent t-test, if p>.05 and there IS equality of variance, which row of values must we read?
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The top row
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Levene’s Test for Equality of Variance - if p<.05, is there equality of variance or not?
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No - there is NOT equality of variance
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Within an independent t-test, if p<.05 and there is NOT equality of variance, which row of values must we read?
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The bottom row
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What is the effect size?
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Effect sizes tell us how much of an effect we can expect to see as a result of the IV being manipulated or the difference between two groups
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According to Cohen, what is regarded as a small effect size?
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0.2
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According to Cohen, what is regarded as a medium effect size?
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0.5
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According to Cohen, what is regarded as a large effect size?
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0.8
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What is a dichotomous variable?
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A variable that only has two levels of measurement, i.e. male or female
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What is the range of Pearson's r?
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-1 to +1
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When a Pearson's r statistic is given, what do the plus or minus signs indicate?
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A positive or negative correlation
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If a Pearson's r statistic is given as 0, what does this indicate?
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That there is no correlation between variables
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If a Pearson's r statistic is given as 1 or -1, what does this indicate?
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A perfect correlation, meaning we can determine one variable simply by knowing the value of the other variable
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What does the Kolmogorov-Smirnov statistic assess?
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The normality of distribution
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In the Kolmogorov-Smirnov statistical test, what does a non-significant result (>0.05) indicate?
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Normality
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If the result of a Kolmogorov-Smirnov statistical test is .000, what does it suggest?
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A violation of the assumption of normality
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Apart from looking at descriptive statistics, how else can we assess normality?
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Skewness and kurtosis
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Is p<.001 significant or not significant?
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Significant
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Is p>.001 significant or not significant?
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Not significant
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Why are parametric tests preferable to non-parametric tests?
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The power efficiency of the nonparametric test is lower than a parametric test
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What are the four main PARAMETRIC tests?
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Indpendent sample T test, two dependent sample T test, ANOVA, Pearson
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What are the four main NON-PARAMETRIC tests?
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Mann Whiteney U Test, Wilcoxon, Kruskal-Wallis, Spearmans
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