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Quant Reasoning

Final Exam

Parametric Tests concern the parameters of a population, assumptions about the parameters of the population, have numerical scores for each individual in the sample, requires data for interval or ratio scales.
Non-Parametric Tests few or any assumptions about the population parameters, subjects are usually classified into categories, do not produce numbers to figure the mean & variances, usually for frequencies, not as sensitive as non-parametric tests, examples of inferential Test
Pearson's r variables are measured on interval or ratio scales, relationship has to be linear, expressed in correlation coefficients (r=0.89 or r=-0.90)
Spearman's p one variable is ordinal, other variable is ordinal, interval or ratio, expressed in correlation coefficients (p=0.56 or p=-0.85)
T-test compares the means of two groups on 1 variable, must use interval or ratio levels of data (DV), must be used if 3 assumptions for parametric are not violated.
Created by: heber.hepworth
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