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رستم پور, مسلم. (1401). مقایسه روش های شناسایی داده های پرت و تاثیر آنها در مطالعات اندازه گیری و ارزیابی مراتع. , 75(4), 639-660. doi: 10.22059/jrwm.2023.350908.1682
مسلم رستم پور. "مقایسه روش های شناسایی داده های پرت و تاثیر آنها در مطالعات اندازه گیری و ارزیابی مراتع". , 75, 4, 1401, 639-660. doi: 10.22059/jrwm.2023.350908.1682
رستم پور, مسلم. (1401). 'مقایسه روش های شناسایی داده های پرت و تاثیر آنها در مطالعات اندازه گیری و ارزیابی مراتع', , 75(4), pp. 639-660. doi: 10.22059/jrwm.2023.350908.1682
رستم پور, مسلم. مقایسه روش های شناسایی داده های پرت و تاثیر آنها در مطالعات اندازه گیری و ارزیابی مراتع. , 1401; 75(4): 639-660. doi: 10.22059/jrwm.2023.350908.1682

مقایسه روش های شناسایی داده های پرت و تاثیر آنها در مطالعات اندازه گیری و ارزیابی مراتع

نشریه علمی - پژوهشی مرتع و آبخیزداری
دوره 75، شماره 4، دی 1401، صفحه 639-660    اصل مقاله (672.35 K)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22059/jrwm.2023.350908.1682
نویسنده
مسلم رستم پور*
استادیار گروه مرتع و آبخیزداری و عضوگروه پژوهشی خشکسالی و تغییر اقلیم، دانشکده منابع طبیعی و محیط زیست، دانشگاه بیرجند، بیرجند، ایران
چکیده
این تحقیق به مقایسه روش‌های شناسایی داده پرت تک متغیره در بین داده‌های درصد پوشش گیاهی در یک مطالعه ارزیابی تاثیر شدت چرا در مراتع مناطق خشک می‌پردازد. بدین منظور، پس از اندازه‌گیری درصد پوشش گیاهی در مرتع و قبل از تحلیل آماری، وجود یا عدم وجود داده پرت به عنوان پیش فرض آزمون‌های پارامتریک فرضیه مقایسه‌ای بررسی شد. در این تحقیق از هشت روش شامل نمودار جعبه‌ای (Boxplot) و دامنه میان چارکی (روش Tukey)، انحراف معیار از میانگین (قانون Three-sigma)، انحراف مطلق از میانه (روش Hampel)، میانگین پیراسته، مقادیر صدک 1 و 99، آزمون کای اسکوئر (χ²)، آزمون گرابز (ESD) و آزمون روزنر (generalised ESD) استفاده شد. نتایج نشان داد که داده‌های درصد پوشش گیاهی مراتع با شدت چرای سبک و متوسط توزیع نرمال ندارند (آزمون شاپیرو-ویلک: 05/0 (P≤. حتی حذف داده پرت نیز منجر به نرمال شدن داده‌ها نشد، اما منجر به همگن شدن واریانس خطا شد (آزمون لیون: 05/0 (P≥. از هشت روش مورد استفاده، روش Z اصلاح شده و آزمون‌های گرابز و روزنر (05/0 (P≥، هیچکدام از داده‌های درصد پوشش گیاهی را به عنوان داده پرت تشخیص ندادند. از بین روش‌های مورد مطالعه، نمودار جعبه‌ای و روش انحراف مطلق از میانه که به میانگین وابسته نیستند، برای داده‌های پوشش گیاهی مناسب‌ترند. از این‌رو قبل از انجام هرگونه آزمون فرضیه مقایسه‌ای، استفاده ترکیبی از دو روش چشمی و آماری برای بررسی وجود یا عدم وجود داده‌های پرت توصیه می‌شود.
کلیدواژه‌ها
آمار پارامتریک؛ پوشش گیاهی؛ داده دورافتاده؛ میانگین؛ مرتع
عنوان مقاله [English]
Comparison of outlier detection methods and their impact on rangeland measurement and Assessment studies
نویسندگان [English]
Moselm Rostampour
Assistant Professor, Department of Rangeland and Watershed Management and Research Group of Drought and Climate Change, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran.
چکیده [English]
This study compared of univariate outlier detection methods among vegetation data in a study of the effect of grazing intensity in the rangelands of arid regions. For this purpose, after measuring the vegetation cover in the rangeland and before the statistical analysis, the presence of outlier data was examined as the assumption of parametric comparison tests. In this study, eight methods including the boxplot and IQR (Tukey method), standard deviation of the mean (three-sigma rule), median absolute deviation (Hampel method), trimmed mean, 1st percentile and 99th percentile, The Chi Square test (χ²), the Grubbs Test (ESD) and the Rosner test (generalized ESD) were used. The results showed that the vegetation cover of rangelands with light and moderate grazing intensity was not normally distributed (Shapiro-Wilk test: p≤0.05). Even deletion of outliers did not lead to a normal distribution, but it resulted in the homogeneity of variances (Levene's test: p≥0.05). The modified Z-score and the Grubbs and Rosner tests (p≥0.05) did not identify outliers from the vegetation cover data. Among the methods evaluated, the boxplot and MAD method, which are not dependent on the mean, are more suitable for the vegetation cover. Therefore, before performing any comparison test, a combination of visual and statistical methods is recommended to evaluate the presence of outliers.
کلیدواژه‌ها [English]
mean, outliers, parametric statistics, rangeland, vegetation
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آمار
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