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

Aykırı değerler, veri kümesinin geri kalanından son derece farklı olan veri noktalarıdır.
Dixon'ın Q-testi, veri setindeki bu tutarsız veri noktalarının korunup korunmayacağını belirlemeye yardımcı olan bir anlamlılık testidir.
Matematiksel olarak, Q-testi istatistiği, aykırı değer ile en yakın veri noktası arasındaki mutlak farkın ve popülasyon aralığının oranıdır.
Q-testi istatistiği veya reddetme katsayısı daha sonra belirli bir anlamlılık düzeyi ve serbestlik dereceleri için tablo haline getirilmiş kritik Q değeri ile karşılaştırılır.
Reddetme katsayısı tablodaki değere eşit veya daha büyük olduğunda, boş hipotez reddedilir ve şüphelenilen aykırı değer reddedilebilir.
Aksine, deneysel değer tablo haline getirilen Q değerinden daha küçük olduğunda sıfır hipotezi kabul edilir. Ardından, şüphelenilen aykırı değerin veri kümesinde tutulması gerekir.

büyük hatanın tespiti: q testi

Bir veya daha fazla veri noktası, verinin geri kalanından uzakta göründüğünde, ölçülen değerin doğru bir şekilde temsil edilmesini sağlamak için bunların aykırı olup olmadığının ve veri setinden çıkarılması gerekip gerekmediğinin belirlenmesine ihtiyaç vardır. Çoğu durumda aykırı değerler büyük hatalardan (veya insan hatalarından) kaynaklanır ve altta yatan olguyu doğru şekilde yansıtmaz. Ancak bazı durumlarda bu belirgin aykırı değerler gerçek fenomenolojik farklılıkları yansıtmaktadır. Bu durumlarda, aykırı değerin tutulup tutulmayacağına karar verilmesine yardımcı olması için istatistiksel yöntemler kullanabiliriz. Aykırı değerleri korumamıza veya reddetmemize yardımcı olabilecek istatistiksel yönteme Q testi denir. Q testini gerçekleştirmek için öncelikle bir veri setindeki değerleri artan değer sırasına göre düzenleriz. Daha sonra bir veri noktası ile ona komşu veri noktası arasındaki mutlak farkın oranını alarak Q değerini hesaplıyoruz. Bu Q değeri daha sonra seçilen bir önem seviyesinde ve uygun serbestlik derecesinde tablo halindeki kritik Q değeriyle karşılaştırılır. Q değeri, tablodaki referans Q değerine eşitse veya bu değeri aşarsa, veri noktası aykırı değer olarak kabul edilir ve bu nedenle veri kümesinden çıkarılır. Burada, sapmanın büyüklüğü rastgele (belirsiz) hatalarla mantıksal olarak açıklanamayacağından, veri noktasını aykırı değer olarak göz ardı etmek mantıklıdır. Öte yandan, Q değeri tablodaki referans değerinden küçükse, veri noktası korunmalıdır ve yorum, bu veri noktası ile verilerin geri kalanı arasındaki farkın makul (istatistiksel) beklenti dahilinde olduğu şeklindedir. .

Büyük Hatanın Tespiti: Q Testi

Aykırı değerler, veri kümesinin geri kalanından son derece farklı olan veri noktalarıdır.
Dixon'ın Q-testi, olup olmadığını belirlemeye yardımcı olan bir anlamlılık testidir ...

Education

JoVE Core

Analytical Chemistry

Analitik Kimya

Unit 1

Ünite 1

Chemical Applications of Statistical Analyses

İstatistiksel Analizlerin Kimyasal Uygulamaları

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

TEMEL TERİMLER VE KAVRAMLAR

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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detection of gross error: the q test

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...

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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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