Name: grubbs test for spotting data outliers
Uploaded: 2024-04-04T10:51:12.000Z
Duration: 1 min 2 s
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Chemistry

CHEM.2

CHEM.2.C

quantifying-and-rejecting-outliers-the-grubbs-test

Quantifying and Rejecting Outliers: The Grubbs Test

Der Grubbs-Test ist, wie der Q-Test von Dixon, ein statistischer Test, um die Ausreißer in Daten mit einer Normalverteilung zu identifizieren. Hier sollte die Anzahl der Beobachtungen gleich oder größer als sieben sein.
Für einen gegebenen Datensatz beinhaltet dieser Test die Berechnung der Grubbs-Statistik G, d. h. des Verhältnisses der absoluten Differenz zwischen dem fragwürdigen Wert und dem Mittelwert zur Standardabweichung der Stichprobe.
Der berechnete G-Wert wird dann mit dem tabellarischen kritischen Wert von G für ein gegebenes Konfidenzniveau und die Anzahl der Beobachtungen verglichen.
Überschreitet der berechnete G-Wert den kritischen Wert von G, wird die fragwürdige Beobachtung als Ausreißer der Daten betrachtet und verworfen. 
Wenn der berechnete G-Wert kleiner als der kritische Wert von G ist, behalten die Daten die fragwürdige Beobachtung bei.

quantifizierung und ablehnung von ausreißern: der grubbs-test

Manchmal kann ein Datensatz eine aufgezeichnete numerische Beobachtung enthalten, die stark vom Rest der Daten abweicht. Unter der Annahme, dass die Daten normalverteilt sind, kann eine statistische Methode namens Grubbs-Test verwendet werden, um festzustellen, ob es sich bei der Beobachtung tatsächlich um einen Ausreißer handelt. Um einen zweiseitigen Grubbs-Test durchzuführen, berechnen Sie zunächst die absolute Differenz zwischen dem Ausreißer und dem Mittelwert. Berechnen Sie dann das Verhältnis zwischen dieser Differenz und der Standardabweichung der Stichprobe. Diese Zahl ist als Grubbs-Statistik „G“ bekannt. Wenn der berechnete G-Wert den kritischen G-Wert für ein bestimmtes Konfidenzniveau und die Anzahl der Beobachtungen überschreitet, wird die fragliche Beobachtung als Ausreißer betrachtet und aus dem Datensatz entfernt. Ist der berechnete G-Wert hingegen kleiner als der kritische G-Wert, wird die fragliche Beobachtung nicht als Ausreißer betrachtet und daher im Datensatz beibehalten.

Quantifizierung und Ablehnung von Ausreißern: Der Grubbs-Test

Der Grubbs-Test ist, wie der Q-Test von Dixon, ein statistischer Test, um die Ausreißer in Daten mit einer Normalverteilung zu identifizieren. Hier ist die Anzahl der ...

Education

Lehre

JoVE Core

Analytical Chemistry

Analytische Chemie

Unit 1

Einheit 1

Chemical Applications of Statistical Analyses

Chemische Anwendungen statistischer Analysen

chemical-applications-of-statistical-analyses

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grubbs test for spotting data outliers

The Grubbs test is a statistical way to spot a possible outlier in a data set. It is used when the data is assumed to follow a normal distribution. A Grubbs test helps decide whether one unusual numerical value should be treated as a true outlier.

To run a two-tailed Grubbs test, first find the absolute difference between the questionable value and the mean. Then divide that difference by the sample standard deviation. The result is the Grubbs statistic, or G.

Next, compare the calculated G value with the G critical value for the chosen confidence level and the number of observations. If the calculated G is larger, the questionable value is considered an outlier and removed from the data set. If the calculated G is smaller, the value is not considered an outlier and is kept in the data set.

Grubbs Test for Spotting Data Outliers

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The Grubbs test is a statistical way to spot a possible outlier in a data set. It is used when the data is assumed to follow a normal distribution. A Grubbs test helps decide whether one unusual numerical value should be treated as a true outlier. To run a two-tailed Grubbs test, first find the absolute difference between the questionable value and the mean. Then divide that difference by the sample standard deviation. The result is the Grubbs statistic, or G. Next, compare the calculated G...

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key terms and concepts

Learn how the Grubbs test checks a normal data set for a possible outlier by comparing the G statistic with the critical value.

Grubbs Test for Spotting Data Outliers | JoVE K12

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Grubbs Test for Spotting Data Outliers

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