Type I and Type II errors and the power of the test when testing the null hypothesis of static range trend are discussed. The consequences associated with Type I and Type II errors are judged to be similar and therefore the probability of committing a Type I or Type II error should be equal. As an example, the current range trend monitoring program for the Moose Camp Allotment on USDA Forest Service land in southwestern Montana is capable of detecting a change in range condition of one condition class 83% of the time when the probability of Type I error is set at .17 (Prob[-Type I Error] = Prob [Type II Error] = .17). Doubling the sample size would increase the ability to detect a condition class change to 95% when the probability of Type I error is set at .05 (Prob[Type I Error] = Prob[Type II Error] = .05). This material was digitized as part of a cooperative project between the Society for Range Management and the University of Arizona Libraries. The Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information. Migrated from OJS platform August 2020
Scholarly peer-reviewed articles published by the Society for Range Management. Access articles on a rolling-window basis from vol. 1, 1948 up to 5 years from the current year. Formerly Journal of Range Management (JRM). More recent content is available by subscription from SRM.