The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 4.693SRF + 45.106SRD 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.

목적: 이 연구는 일반선형모형에서 이분산성의 특성을 계량적으로 설명하고, 경험적 예시를 통한 다양한 통계적 방법을 비교하여 이분산성의 확인 및 해결을 위한 일련의 절차를 설명고자 한다. 본론: 남, 여 중학생 185명의 자료를 이용하여 경험적 예시모형을 이용하여 이분산성의 확인 및 해결 방안을 위한 실질적 데이터 분석 방법을 구체적으로 제시하였다. 결론: 스포츠심리학연구에서 이분산성의 문제와 해결 그리고 논의의 필요성에 대하여 논 의하였다.