General steps in correlational analysis

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In correlational analysis we are asking the general question:
"To what extent are two variables related (dependent) or unrelated (independent)?"
More specifically, in the case of linear correlation, we are asking the question:
"To what extent do two variables exhibit a linear relationship?"
Recommended steps for conducting correlational analyses are:
 Determine the level of measurement for each variable.
 Examine univariate descriptive statistics and graphical displays for each variable, paying particular attention to the sample size (N >= 50; VanVoorhis & Morgan, 2007), frequencies, central tendency, and distribution of responses.
 Recode if necessary (e.g., if there are too few responses for a response option or data is not normally distributed).
 Examine a bivariate graph (e.g,. clustered bar graph or scatterplot)
 Examine bivariate descriptive statistics if variables are discrete (i.e., crosstabs or contingency tables)
 Examine relevant correlational statistics, including indicators of size (e.g., Phi, Cramer's ν, Point biserial, Spearman's Rho or Kendall's Tau, or productmoment correlation (r)) and statistical significance of the relationship
 Interpret/conclude  Explain, in clear, simple language, what the correlational analysis indicates about the relationship (direction, strength, and significance) between the constructs of interest.

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