ABSTRACT
This chapter examines measures of association as well as inferences involving measures of association. Methods for directly determining the relationship among two variables are known as bivariate analysis, rather than univariate analysis, which are only concerned with a single variable. It discusses Pearson product-moment correlation coefficient, inferences about the Pearson product-moment correlation coefficient, some issues regarding correlations, other measures of association, Statistical Package for Social Sciences and R. These measures of association allow us to determine how two variables are related to one another and can be useful in two applications: as a descriptive statistic by itself and as an inferential test. The scatterplot allows the researcher to evaluate the direction and the strength of the relationship among X and Y. The direction of the relationship has to do with whether the relationship is positive or negative. The chapter concludes with a template and an American Psychological Association-style paragraph detailing the results from an example dataset.
