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  • Created by: Chloe
  • Created on: 29-04-15 19:02
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  • Correlation
    • Multivariate: analyses that have more than one DV
    • Bivariate: correlation & regression analysis which have two variables that are technically both DV's
    • Regression: identifying which variables are effective at predicting other variables of interest
    • Correlations show the degree of relationship between variables X & Y
    • Strength of a relationship is measured by the correlation coefficient (r) - varies from 0-1 (+/-)
    • The Main Assumptions of Pearsons R:                 (1) Homogenity of variance: the variance of Y is the same at all levels of X   (2) Normality: that both X & Y samples come from populations having normal distributions (3) Linearity of regression: that the underlying relationships can be adequately summarised by a straight line & not a curve
    • Coefficient of determination: an estimate of the proportion of variability in one variance that can be determined from knowledge of the other - The square of the pearson correlation coefficient (R^2)
      • A strong relationship = one which accounts for more than 50% of variation in the criterion variable (R= .7 or more)
        • A Moderate relationship = 16%-36% (R= ,4 - .6)


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