Abstract
Selected statistical procedures used in the analysis of research data are presented. The relationship of significance testing to research hypotheses is explained in terms of tests of differences and correlation. Also, the differences, assumptions, and advantages and disadvantages of parametric and nonparametric statistics are discussed. With regard to each statistic presented, emphasis is placed on the hypotheses that would be tested, the kinds of data for which the statistic is appropriate, the method of calculation, and how to test for "significance." The selected statistical procedures include the Student's t-test and chi square. An explanation of the concept of correlation is provided, and several correlation coefficients are discussed, including the Pearson r, Spearman rho, Kendall's tau, the point biserial, biserial, phi coefficient, and contingency coefficient. Pharmacists must know basic statistical procedures in order to be able to effectively interpret the results of published research or to appropriately analyze data that have been collected in their own research endeavors.
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