ASTM E178 PDF

Buy ASTM E PRACTICE FOR DEALING WITH OUTLYING OBSERVATIONS from SAI Global. 1, Outlier Calculator ASTM E 2, No. Data, Avgerage, Round to: Test Result. 3, 1, , , 3, Gmm. 4, 2, , Significant digits *, Gmm. 5, 3, , # of. Purchase your copy of ASTM E – 16A as a PDF download or hard copy directly from the official BSI Shop. All BSI British Standards available.

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An outlying observation, or outlier, is one that appears to deviate markedly e17 other members of the sample in which it occurs. Please login to your authorized staff account to use this feature.

The examples are not binding on products or test methods treated. ASTM does not give any warranty express or implied or make any representation that the contents of this abstract are accurate, complete or up to date. Register for a trial account. Nevertheless, the tests suggested do cover a wide enough range of cases in practice to have broad utility. In this connection, the following two alternatives are of interest: Recommended criteria and illustrations d178 single samples including the Dixon criteria which are based entirely on ratios of differences between the observations, criterion using independent standard deviation, and criterion for known standard deviation are presented.

It is informational only and not an official part of the standard; the full text of the standard itself must be referred to for its use and application. As the voice of the U.

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This standard is also available to be included in Standards Subscriptions. If you like to setup a quick demo, let us know at support madcad. Standards Subsctiption may be the perfect solution. Print 1 2 3 4 5 page sstarting from page current e18.

ASTM E178 – 16A

In this connection, the following two alternatives are of interest: It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory requirements prior to use. E Standard Practice for Certificate Programs.

An outlying observation, or outlier, is one that appears to deviate markedly from other members of the sample in s178 it occurs. The boldface numbers in parentheses refer to a list of references at the end of this standard. In such cases, ee178 may be desirable to institute an investigation to ascertain the reason for the aberrant value. This practice covers outlying observations in samples and how to test the statistical significance of them.

ASTM E – 16 Standard Practice for Dealing With Outlying Observations

An outlying observation, or “outlier,” is asfm that appears to deviate markedly from other members of the sample in which it occurs. At any rate, in subsequent data analysis, the outlier or outliers will be recognized as probably being from a different population than that of the other sample values.

In this connection, the following two alternatives are of interest:. We have no amendments or corrections for this standard.

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Subscription pricing is determined by: Referenced Documents purchase separately The documents listed below are referenced within the subject standard but are not provided as part of the standard. This practice covers outlying observations in samples and how to test the statistical significance of them. At any rate, in subsequent data analysis, the outlier e78 outliers will be recognized as probably being from a different population than that of the other sample values.

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ASTM E – 16a Standard Practice for Dealing With Outlying Observations

Abstract This practice covers outlying observations in samples and how to test the statistical significance of them. If the document is asm or amended, you will be notified astj email. At any rate, in subsequent data analysis the outlier or outliers will be recognized as probably being from a different population than that of the other sample values. Link to Active This link will always route to the current Active version of the standard.

Historical Version s – view previous versions of standard.

The procedures covered herein apply primarily to the simplest kind of experimental data, that is, replicate measurements of some property of a given material, or observations in a supposedly single random sample.