Statistical analysis in equine research involves the application of mathematical techniques to collect, review, and interpret data related to horse health, behavior, and performance. This field encompasses a variety of methods, including descriptive statistics, inferential statistics, and multivariate analysis, to identify patterns, test hypotheses, and draw conclusions from equine data. Statistical analysis aids in understanding various aspects of equine science, such as disease prevalence, treatment efficacy, genetic traits, and performance metrics. This page aggregates peer-reviewed research studies and scholarly articles that explore the methodologies, applications, and outcomes of statistical analysis in the context of equine studies.
To evaluate the effect of four recumbent body positions on intraocular pressure (IOP) in anesthetized normal horses. Methods: Ten nonglaucomatous adult horses. Methods: Intraocular pressure was measured with a rebound tonometer in both eyes of standing sedated horses (baseline), then under general anesthesia during four randomized recumbent body positions, including Trendelenburg (Tr; 15-degree head down), reverse Trendelenburg (RTr; 15-degree head up), dorsal, and lateral; only the superior eye was measured in lateral positions. The mean of 3 IOP readings was taken at each position, allowing ...
Zanchi M, Bordin C, Ablondi M, Asti V, Summer A, Valle E, Ozella L.Early identification of sport potential in show jumping horses remains challenging because competition outcomes vary widely, and elite-level performance develops after considerable time. In this study, we evaluated the applicability of machine learning approaches to competition records from horses identified through FEI participation, complemented by national-level records from Sweden, Belgium and France, with the aim of identifying horses likely to reach elite performance. Performance data from Fédération Équestre Internationale (FEI) competitions were analysed using an Extreme Gradient Bo...