A multivariate analysis of certain biochemical components of equine and feline serum samples as reported by an auto-analyzer system.

Abstract

This thesis contains a multivariate statistical analysis of the results of an automated analysis of serum samples from the horse and cat. In the horse, 12 biochemical components plus body weight and age are recorded; thus, observations are made on 14 random variables. In the case of the cat there are observations on 13 random variables. Ninety-one (91) pair-wise correlation coefficients are computed from the equine data and 78 pair-wise correlation coefficients are computed from the feline data. Extensive hypothesis testing concerning these correlation coefficients is conducted and the results are presented. A discriminant analysis for 2 groups, male and female, is conducted for each species. In this analysis the vector of sample means of the biochemical components plus body weight and age for males is contrasted with the corresponding vector from females. Tolerance limits for each biochemical component measured are presented for both species.