Abstract
This chapter focuses on correlation analysis. Correlation coefficients are used to determine whether a relationship exists between sets of two variables. Measures of correlation help in determining whether there is a pattern to a set of data. Correlation coefficients give a numerical value that summarizes the strength and direction of the relationship between two variables. Various correlation coefficients are used to analyze data, depending on whether the data are nominal, ordinal, interval, or ratio in scale. In quick analysis, gamma or Yule's Q is a useful correlation measure when data can be structured in ordinal form. Gamma can also be applied to higher level (interval or ratio) data, which have been categorized as ordinal data. Gamma is especially useful when data are available in tabular form and when it is to be determined whether there is a correlation between the variables. The value of gamma is determined by computing the relationship between the number of pairs of observations having the same ranking on the two variables and the number of pairs of observations having the opposite rankings on the two variables.
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