Name: using the q test to flag outlier data
Uploaded: 2024-04-04T10:51:12.000Z
Duration: 1 min
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Chemistry

CHEM.2

CHEM.2.C

Detection of Gross Error: The Q Test

القيم المتطرفة هي نقاط البيانات تلك التي تختلف اختلافا كبيرا عن بقية مجموعة البيانات.
اختبار Q من ديكسون هو اختبار دلالة يساعد في تحديد ما إذا كان سيتم الاحتفاظ بنقاط البيانات غير المتسقة هذه أو رفضها في مجموعة البيانات.
رياضيا ، إحصائية اختبار Q هي نسبة الفرق المطلق بين القيم المتطرفة إلى أقرب نقطة بيانات ونطاق السكان.
ثم تتم مقارنة إحصائية اختبار Q أو حاصل الرفض بقيمة Q الحرجة المجدولة لمستوى أهمية معين ودرجات الحرية.
عندما يكون حاصل الرفض مساويا أو أكبر من القيمة المجدولة ، يتم رفض الفرضية الصفرية ، ويمكن رفض القيم المتطرفة المشتبه بها.
على العكس من ذلك ، يتم قبول الفرضية الصفرية عندما تكون القيمة التجريبية أصغر من قيمة Q المجدولة. بعد ذلك ، يجب الاحتفاظ بالقيم الخارجية المشتبه بها في مجموعة البيانات.

اكتشاف الخطأ الجسيم: اختبار q

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عندما تظهر نقطة بيانات واحدة أو أكثر بعيدًا عن بقية البيانات، تكون هناك حاجة لتحديد ما إذا كانت قيمًا متطرفة وما إذا كان ينبغي حذفها من مجموعة البيانات لضمان تمثيل دقيق للقيمة المقاسة. في كثير من الحالات، تنشأ القيم المتطرفة من أخطاء جسيمة (أو أخطاء بشرية) ولا تعكس بدقة الظاهرة الأساسية. ومع ذلك، في بعض الحالات، تعكس هذه القيم المتطرفة الاختلافات الظاهرية الحقيقية. في هذه الحالات، يمكننا استخدام الأساليب الإحصائية للمساعدة في تحديد ما إذا كان سيتم الاحتفاظ بالقيمة المتطرفة أم لا. تسمى الطريقة الإحصائية التي يمكن أن تساعدنا في الاحتفاظ بالقيم المتطرفة أو رفضها باختبار Q. لإجراء اختبار Q، نقوم أولاً بترتيب القيم في مجموعة البيانات من أجل زيادة القيمة. ثم نحسب قيمة Q عن طريق أخذ نسبة الفرق المطلق بين نقطة البيانات ونقطة البيانات المجاورة لها. ثم تتم مقارنة قيمة Q هذه بقيمة Q الحرجة المجدولة عند مستوى أهمية مختار ودرجات حرية مناسبة. إذا كانت قيمة Q تساوي أو تتجاوز قيمة Q المرجعية في الجدول، فإن نقطة البيانات تعتبر قيمة شاذة وبالتالي يتم رفضها من مجموعة البيانات. هنا، من المعقول تجاهل نقطة البيانات باعتبارها نقطة متطرفة لأن حجم الانحراف لا يمكن حسابه منطقيًا عن طريق الأخطاء العشوائية (غير المحددة). ومن ناحية أخرى، إذا كانت قيمة Q أصغر من القيمة المرجعية في الجدول، فيجب الاحتفاظ بنقطة البيانات، والتفسير هو أن الفرق بين نقطة البيانات هذه وبقية البيانات ضمن التوقع المعقول (الإحصائي) .
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اكتشاف الخطأ الجسيم: اختبار Q

القيم المتطرفة هي نقاط البيانات تلك التي تختلف اختلافا كبيرا عن بقية مجموعة البيانات.
اختبار Q من ديكسون هو اختبار أهمية يساعد في تحديد ما إذا كان ...

Education

JoVE Core

Analytical Chemistry

الكيمياء التحليلية

Unit 1

الوحدة الأولى

Chemical Applications of Statistical Analyses

التطبيقات الكيميائية للتحليلات الإحصائية

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

المصطلحات والمفاهيم الأساسية

using the q test to flag outlier data

The Q test helps identify outlier data points that sit far from the rest of a data set. In high school lab work, this can help students decide whether an unusual value should stay in the data or be removed. Outliers often come from gross errors, or human mistakes, and may not reflect the real result being measured.

Some points that look like outliers may still reflect a true difference in the phenomenon being studied. In those cases, a statistical test can help judge whether the value should be kept or rejected. The Q test provides that check by comparing a suspect point with the rest of the ordered data.

To perform the Q test, the values are first arranged in increasing order. Next, the Q value is calculated as the ratio of the absolute difference between a data point and its adjacent data point. That Q value is then compared with the tabulated critical Q value for a chosen significance level and the correct degrees of freedom.

If the calculated Q value is equal to or greater than the table value, the point is treated as an outlier and rejected from the data set. In that case, the deviation is considered too large to be explained by random, indeterminate errors. If the Q value is smaller than the reference value, the point is retained because the difference is within normal statistical expectation.

Using the Q Test to Flag Outlier Data

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key terms and concepts

Learn how the Q test helps students identify outlier data, compare a suspected value to a critical table value, and decide whether to keep or reject it.

Using the Q Test to Flag Outlier Data | JoVE K12

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Using the Q Test to Flag Outlier Data

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