Recent studies have noted the inadequacy of the Carnegie Commission's classification category of Liberal Arts Colleges II. This study was designed to develop a more definitive taxonomy for the private colleges in this category based on their financial characteristics.

The institutional population for this study consisted of 499 private colleges classified as Liberal Arts Colleges II that were in operation during the fiscal year 1973-74. A computer tape of REGIS IX data provided by the National Center for Educational Statistics,"Financial Statistics of Institutions of Higher Education 1974," was utilized for the collection of data and computation of specific measures.

Twelve financial variables were selected and each variable was divided by the college's fall 1973-74 FTE student enrollment and the quotient was used as the ratio for this study. This procedure was used to express the financial data in terms of the enrollment of each institution.

The NORMIX cluster analysis was used to analyze these per FTE ratios to determine if sub-classifications of colleges existed within the total population of 499 colleges. The NORMIX analysis produced 13 clusters of colleges. Each of the 13 clusters was reviewed to determine its financial characteristic and to assess the discriminating importance of the ratios. To facilitate this inspection of the ratios, the mean of each ratio was plotted graphically to explain important deviations from the corresponding ratio for the population of 499 colleges. In addition, characteristic data for each cluster was reviewed.

The discussion of results presented several conclusions, implications, and recommendations for further research. A number of financial strategy considerations were reviewed for the various clusters of colleges. In addition, the enrollment strategy of various colleges was examined.

The cluster analysis technique as used in this study has additional possible uses. First, the system does allow for taxonomy construction based on the variables specified by the researcher. Second, the technique can be used to help edit data. Third, the method could be helpful in determining the mission and academic quality of colleges if additional characteristic data were included in the clustering process.

The technique of financial analysis used in this study suggested topics for further research. The computerized systems available today open new horizons for future researchers.