Data sets from research in clinical practice professions often do not meet assumptions necessary for appropriate use of parametric statistics (Lezak and Gray, 1984). When assumptions underlying the use of the parametric tests are violated or cannot be documented, the power of the parametric test may be invalidated and consequently, the significance levels inaccurate (Gibbons, 1976). Much research has investigated the relative merits of parametric versus nonparametric procedures using simulation studies, but little has been done using actual data sets from a particular discipline. This study compared the application of parametric and nonparametric statistics using a body of literature in clinical occupational therapy. The most common parametric procedures in occupational therapy research literature from 1980 - 1984 were identified using methodology adapted from Goodwin and Goodwin (1985). Five small sample size data sets from published occupational therapy research articles typifying the most commonly used univariate parametric procedures were obtained, and subjected to exploratory data analyses (Tukey, 1977) in order to evaluate whether or not assumptions underlying appropriate use of the respective parametric procedures had been met. Subsequently, the nonparametric analogue test was identified and computed. Results revealed that in three of the five cases (paired t-test, one factor ANOVA and Pearson Correlation Coefficient) assumptions underlying the use of the parametric test were not met. In one case (independent t-test) the assumptions were met with a minor qualification. In only one case (simple linear regression) were assumptions clearly met. It was also found that in each of the two cases where parametric assumptions were met, no significant differences in p values between the parametric and the nonparametric tests were found. And conversely, in each of the three cases where parametric assumptions were not met, significant differences between the parametric and nonparametric results were found. These findings indicate that if cases were considered as a whole, there was a one hundred percent agreement between whether or not parametric assumptions were violated and whether or not differences were discovered regarding parametric versus nonparametric results. Other findings regarding (a) non-normality, (b) outliers, (c) multiple violation of assumptions for a given procedure, and (d) research designs employed are discussed and implications identified. Suggestions for future research are put forth. / Ph. D.