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ASTM E2943-14

(Guide)

Standard Guide for Two-Sample Acceptance and Preference Testing with Consumers

Standard Guide for Two-Sample Acceptance and Preference Testing with Consumers

SIGNIFICANCE AND USE
5.1 Acceptance and preference are the key measurements taken in consumer product testing as either a new product idea is developed into testable prototypes or existing products are evaluated for potential improvements, cost reductions, or other business reasons. Developing products that are preferred overall, or liked as well as, or better, on average, compared to a standard or a competitor, among a defined target consumer group, is usually the main goal of the product development process. Thus, it is necessary to test the consumer acceptability or the preference of a product or prototype compared to other prototypes or potential products, a standard product, or other products in the market. The researcher, with input from her/his stakeholders, has the responsibility to choose appropriate comparison products and scaling or test methods to evaluate them. In the case of a new-to-the-world product, there may or may not be a relevant product for comparison. In this case, a benchmark score or rating may be used to determine acceptability. A product or prototype that is acceptable to the target consumer is one that meets a minimum criterion for liking, and a product that is preferred over an existing product has the potential to be chosen more often than the less-preferred product by the consumer in the marketplace, when all other factors are equal.  
5.2 The external validity (the extent to which the results of a study can be generalized) of both acceptance and preference measures to manage decision risk at all stages of the development cycle is dependent on the ability of the researcher to generalize the results from the respondent sample to the target population at large. This depends both upon the sample of respondents and the way the test is constructed. Within the context of a single test, acceptance measures tell the relative hedonic status of the two samples, quantitatively, as well as where on the hedonic continuum each of the samples falls, that is, “disliked,”...
SCOPE
1.1 This guide covers acceptance and preference measures when each is used in an unbranded, two-sample, product test. Each measure, acceptance, and preference, may be used alone or together in a single test or separated by time. This guide covers how to establish a product’s hedonic or choice status based on sensory attributes alone, rather than brand, positioning, imagery, packaging, pricing, emotional-cultural responses, or other nonsensory aspects of the product. The most commonly used measures of acceptance and preference will be covered, that is, product liking overall as measured by the nine-point hedonic scale and preference measured by choice, either two-alternative forced choice or two-alternative with a “no preference” option.  
1.2 Three of the biggest challenges in measuring a product’s hedonic (overall liking or acceptability) or choice status (preference selection) are determining how many respondents and who to include in the respondent sample, setting up the questioning sequence, and interpreting the data to make product decisions.  
1.3 This guide covers:  
1.3.1 Definition of each type of measure,  
1.3.2 Discussion of the advantages and disadvantages of each,  
1.3.3 When to use each,  
1.3.4 Practical considerations in test execution,  
1.3.5 Risks associated with each,  
1.3.6 Relationship between the two when administered in the same test, and  
1.3.7 Recommended interpretations of results for product decisions.  
1.4 The intended audience for this guide is the sensory consumer professional or marketing research professional (“the researcher”) who is designing, executing, and interpreting data from product tests with acceptance or choice measures, or both.  
1.5 Only two-sample product tests will be covered in this guide. However, the issues and recommended practices raised in this guide often apply to multi-sample tests as well. Detailed coverage of execution tactics, optional types of s...

General Information

Status
Historical
Publication Date
31-Aug-2014
ICS
19.020 - Test conditions and procedures in general
Technical Committee
E18 - Sensory Evaluation
Drafting Committee
E18.04 - Test Methods
Current Stage
Ref Project

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ASTM E2943-14 - Standard Guide for Two-Sample Acceptance and Preference Testing with ConsumersASTM E2943-14 - Standard Guide for Two-Sample Acceptance and Preference Testing with Consumers
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ASTM E2943-14 - Standard Guide for Two-Sample Acceptance and Preference Testing with Consumers
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NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
Contact ASTM International (www.astm.org) for the latest information
Designation: E2943 − 14
StandardGuide for
Two-Sample Acceptance and Preference Testing with
1
Consumers
This standard is issued under the fixed designation E2943; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
INTRODUCTION
This guide is intended to be used by sensory consumer and marketing research professionals
(referredtoasthe“researcher”or“researchprofessional”)asanaidtounderstandingissuesassociated
with and to conducting two-sample acceptance and preference tests with consumers. This guide
includes a general summary of considerations and practices for conducting hedonic tests followed by
specific considerations and practices for both acceptance and preference testing, including pros and
cons of each method. Final sections consider the incorporation of both acceptance and preference
testing into the research plan and discuss potential lack of linkage in output/results between them. A
flowchart outlining summary of these methods and references for further reading are also included.
1. Scope 1.3.1 Definition of each type of measure,
1.3.2 Discussion of the advantages and disadvantages of
1.1 This guide covers acceptance and preference measures
each,
when each is used in an unbranded, two-sample, product test.
1.3.3 When to use each,
Each measure, acceptance, and preference, may be used alone
1.3.4 Practical considerations in test execution,
or together in a single test or separated by time. This guide
1.3.5 Risks associated with each,
covers how to establish a product’s hedonic or choice status
1.3.6 Relationship between the two when administered in
based on sensory attributes alone, rather than brand,
the same test, and
positioning, imagery, packaging, pricing, emotional-cultural
1.3.7 Recommended interpretations of results for product
responses, or other nonsensory aspects of the product. The
decisions.
most commonly used measures of acceptance and preference
will be covered, that is, product liking overall as measured by
1.4 The intended audience for this guide is the sensory
the nine-point hedonic scale and preference measured by consumerprofessionalormarketingresearchprofessional(“the
choice, either two-alternative forced choice or two-alternative
researcher”) who is designing, executing, and interpreting data
with a “no preference” option. fromproducttestswithacceptanceorchoicemeasures,orboth.
1.2 Threeofthebiggestchallengesinmeasuringaproduct’s
1.5 Only two-sample product tests will be covered in this
hedonic (overall liking or acceptability) or choice status guide. However, the issues and recommended practices raised
(preference selection) are determining how many respondents
in this guide often apply to multi-sample tests as well. Detailed
and who to include in the respondent sample, setting up the
coverage of execution tactics, optional types of scales, various
questioning sequence, and interpreting the data to make prod-
approaches to data analysis, and extensive discussions of the
uct decisions.
reliability and validity of these measures are all outside of the
scope of this guide.
1.3 This guide covers:
1.6 Units—The values stated in SI units are to be regarded
1
as the standard. No other units of measurement are included in
This guide is under the jurisdiction of ASTM Committee E18 on Sensory
Evaluation and is the direct responsibility of Subcommittee E18.04 on Fundamen- this standard.
tals of Sensory.
1.7 This standard does not purport to address all of the
Current edition approved Sept. 1, 2014. Published September 2014. DOI:
safety concerns, if any, associated with its use. It is the
10.1520/E2943-14.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
1

---------------------- Page: 1 ----------------------
E2943 − 14
responsibility of the user of this standard to establish appro- (SD). The individual statements are either clearly favorable or
priate safety and health practices and determine the applica- clearly unfavorable (2 and 3).
bility of regulatory limitations prior to use.
3.2.6 P ,n—used in forced choice preference measures; a
max
test sensitivity parameter established before testing and used
2. Referenced Documents
along with the selected values of α and β to determine the
2
2.1 ASTM Standards: number of respondents needed in a study.
E253 Terminology Relating to Sensory Evaluation of Mate-
3.2.6.1 Discussion—P is the proportion of common re-
max
rials and Products sponses that the researcher wants the test to be able to detect
E456 Terminology Relating to Quality and Statistics
with a probability of 1 –β.
...

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Standard Guide for Two-Sample Acceptance and Preference Testing With Consumers

SIGNIFICANCE AND USE
5.1 Acceptance and preference are the key measurements taken in consumer product testing as either a new product idea is developed into testable prototypes or existing products are evaluated for potential improvements, cost reductions, or other business reasons. Developing products that are preferred overall, or liked as well as, or better, on average, compared to a standard or a competitor, among a defined target consumer group, is usually the main goal of the product development process. Thus, it is necessary to test the consumer acceptability or the preference of a product or prototype compared to other prototypes or potential products, a standard product, or other products in the market. The researcher, with input from her/his stakeholders, has the responsibility to choose appropriate comparison products and scaling or test methods to evaluate them. In the case of a new-to-the-world product, there may or may not be a relevant product for comparison. In this case, a benchmark score or rating may be used to determine acceptability. A product or prototype that is acceptable to the target consumer is one that meets a minimum criterion for liking, and a product that is preferred over an existing product has the potential to be chosen more often than the less-preferred product by the consumer in the marketplace, when all other factors are equal.  
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1.1 This guide covers acceptance and preference measures when each is used in an unbranded, two-sample, product test. Each measure, acceptance, and preference, may be used alone or together in a single test or separated by time. This guide covers how to establish a product’s hedonic or choice status based on sensory attributes alone, rather than brand, positioning, imagery, packaging, pricing, emotional-cultural responses, or other nonsensory aspects of the product. The most commonly used measures of acceptance and preference will be covered, that is, product liking overall as measured by the nine-point hedonic scale and preference measured by choice, either two-alternative forced choice or two-alternative with a “no preference” option.  
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1.3 This guide covers:  
1.3.1 Definition of each type of measure,  
1.3.2 Discussion of the advantages and disadvantages of each,  
1.3.3 When to use each,  
1.3.4 Practical considerations in test execution,  
1.3.5 Risks associated with each,  
1.3.6 Relationship between the two when administered in the same test, and  
1.3.7 Recommended interpretations of results for product decisions.  
1.4 The intended audience for this guide is the sensory consumer professional or marketing research professional (“the researcher”) who is designing, executing, and interpreting data from product tests with acceptance or choice measures, or both.  
1.5 Only two-sample product tests will be covered in this guide. However, the issues and recommended practices raised in this guide often apply to multi-sample tests as well. Detailed coverage of execution tactics, optional types of s...

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4.1 Using best practices for SGPE ensures that decisions made will be based on scientific principles, and the outputs obtained will be more objective than those evaluation sessions conducted without this planning, structure, focus, and best practices. These small group evaluations contrast with more formal product tests that include a prequalified participant sample, hypothesis testing, and statistical analysis. Without best sensory practices and procedures, SGPE may be unstructured, unsystematic, difficult to manage, and may lead to outputs that are unclear, not credible, or ignored. Additionally, the use of proper sensory practices reduces bias among participants with specific sample knowledge or a desire to advance an agenda. This guide provides a framework for conceptualizing, organizing, and executing these SGPE.  
4.2 SGPE are used in situations in which formal, hypothesis-driven product evaluations are not required. These include situations in which the decision risk is small or stakeholders feel comfortable in making a decision with the attendant risks, or both. Examples of these situations may include limited availability of samples or other resources, potential patent exposure, or low incidence of target population. The SGPE could be an initial screening step or a precursor test before a more formal product test. In the proper context, SGPE can also be a decision-making tool in and of itself. Using the framework presented here provides a degree of rigor that may be absent when a few people evaluate a product without controlled conditions. A poster presented at the 2009 Pangborn Sensory Science Symposium (1)3 reported the results of a survey on SGPE. 59 % of respondents (N = 92) stated that, at their place of employment, typically, non-sensory professionals organized SGPE. Table 1 summarizes key differences between a typical unstructured product evaluation with a small group not following best practices and an SGPE that follows the best practices outlined...
SCOPE
1.1 This guide covers those occasions in which a small group of individuals (generally between three and ten) with potentially different functional roles and degrees of training in sensory and product evaluation, evaluates a product or series of products for a specific objective, with a pre-identified decision to be made, but without the use of formal hypothesis testing or statistics. In the product testing industry, these are often referred to as “benchings,” “cuttings,” or “bench screenings” or, in the case of food products, “tastings,” “informal tastings,” “team tastings,” or “technical tastings.” In this guide, the term “Small Group Product Evaluation” (SGPE) is used.  
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Standard Test Method for Directional Difference Test

SIGNIFICANCE AND USE
5.1 The directional difference test determines with a given confidence level whether or not there is a perceivable difference in the intensity of a specified attribute between two samples, for example, when a change is made in an ingredient, a process, packaging, handling, or storage.  
5.2 The directional difference test is inappropriate when evaluating products with sensory characteristics that are not easily specified, not commonly understood, or not known in advance. Other difference test methods such as the same-different test should be used.  
5.3 A result of no significant difference in a specific attribute does not ensure that there are no differences between the two samples in other attributes or characteristics, nor does it indicate that the attribute is the same for both samples. It may merely indicate that the degree of difference is too low to be detected with the sensitivity (α, β, and Pmax) chosen for the test.  
5.3.1 The method itself does not change whether the purpose of the test is to determine that two samples are perceivably different versus that the samples are not perceivably different. Only the selected values of Pmax, α, and β change. If the objective of the test is to determine if the two samples are perceivably different, then the value selected for α is typically smaller than the value selected for β. If the objective is to determine if no perceivable difference exists, then the value selected for β is typically smaller than the value selected for α and the value of Pmax needs to be stated explicitly.
SCOPE
1.1 This test method covers a procedure for comparing two products using a two-alternative forced-choice task.  
1.2 This method is sometimes referred to as a paired comparison test or as a 2-AFC (alternative forced choice) test.  
1.3 A directional difference test determines whether a difference exists in the perceived intensity of a specified sensory attribute between two samples.  
1.4 Directional difference testing is limited in its application to a specified sensory attribute and does not directly determine the magnitude of the difference for that specific attribute. Assessors must be able to recognize and understand the specified attribute. A lack of difference in the specified attribute does not imply that no overall difference exists.  
1.5 This test method does not address preference.  
1.6 A directional difference test is a simple task for assessors, and is used when sensory fatigue or carryover is a concern. The directional difference test does not exhibit the same level of fatigue, carryover, or adaptation as multiple sample tests such as triangle or duo-trio tests. For detail on comparisons among the various difference tests, see Ennis (1), MacRae (2), and O'Mahony and Odbert (3).2  
1.7 The procedure of the test described in this document consists of presenting a single pair of samples to the assessors.  
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This guide identifies statistical procedures for use in developing new test methods or revising or evaluating existing test methods, or both. It also cites statistical procedures especially useful in the application of test methods. This standard recommends what approaches may be taken and indicates which standards may be used to perform such assessments.
SIGNIFICANCE AND USE
4.1 The creation of a standardized test method generally follows a series of steps from inception to approval and ongoing use. In all such stages there are questions of how well the test method performs.  
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4.2 This standard introduces a series of phases which are recommended to be considered during the life cycle of a test method as depicted in Fig. 1. These begin with a design phase where the standard is initially prepared. A development phase involves a variety of experiments that allow further refinement and understanding of how the test method performs within a laboratory. In an evaluation phase the test method is then examined by way of interlaboratory studies resulting in precision and bias statistics which are published in the standard. Finally, the test method is subject to a monitoring phase.
FIG. 1 Sequence of Steps  
4.3 All ASTM test methods are required to include statements on precision and bias.3  
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SCOPE
1.1 This guide identifies statistical procedures for use in developing new test methods or revising or evaluating existing test methods, or both.  
1.2 This guide also cites statistical procedures especially useful in the application of test methods.  
1.3 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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Standard Guide for Sampling Design

ABSTRACT
This guide defines terms and introduces basic methods for probability sampling of discrete populations, areas, and bulk materials. It provides an overview of common probability sampling methods employed by users of ASTM standards. This guide also describes the principal types of sampling designs and provides formulas for estimating population means and standard errors of the estimates.
SIGNIFICANCE AND USE
4.1 This guide describes the principal types of sampling designs and provides formulas for estimating population means and standard errors of the estimates. Practice E105 provides principles for designing probability sampling plans in relation to the objectives of study, costs, and practical constraints. Practice E122 aids in specifying the required sample size. Practice E141 describes conditions to ensure validity of the results of sampling. Further description of the designs and formulas in this guide, and beyond it, can be found in textbooks (1-10).3  
4.2 Sampling, both discrete and bulk, is a clerical and physical operation. It generally involves training enumerators and technicians to use maps, directories and stop watches so as to locate designated sampling units. Once a sampling unit is located at its address, discrete sampling and area sampling enumeration proceeds to a measurement. For bulk sampling, material is extracted into a composite.  
4.3 A sampling plan consists of instructions telling how to list addresses and how to select the addresses to be measured or extracted. A frame is a listing of addresses each of which is indexed by a single integer or by an n-tuple (several integer) number. The sampled population consists of all addresses in the frame that can actually be selected and measured. It is sometimes different from a targeted population that the user would have preferred to be covered.  
4.4 A selection scheme designates which indexes constitute the sample. If certified random numbers completely control the selection scheme the sample is called a probability sample. Certified random numbers are those generated either from a table (for example, Ref (11)) that has been tested for equal digit frequencies and for serial independence, from a computer program that was checked to have a long cycle length, or from a random physical method such as tossing of a coin or a casino-quality spinner.  
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SCOPE
1.1 This guide defines terms and introduces basic methods for probability sampling of discrete populations, areas, and bulk materials. It provides an overview of common probability sampling methods employed by users of ASTM standards.  
1.2 Sampling may be done for the purpose of estimation, of comparison between parts of a sampled population, or for acceptance of lots. Sampling is also used for the purpose of auditing information obtained from complete enumeration of the population.  
1.3 No system of units is specified in this standard.  
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ABSTRACT
The purpose of this guide is to provide guidelines for identifying the elements that comprise the test result of a test method and to illustrate how these elements combine into the test result. It covers the types of measurement scales used for expressing observations and test results. This guide provides information on the construction of test results from more elemental measurements.
SIGNIFICANCE AND USE
4.1 All test methods have an output in the form of a test result. This guide provides information on the construction of test results from more elemental measurements.  
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SCOPE
1.1 This standard provides guidelines for identifying the elements that comprise the test result of a test method and to illustrate how these elements combine into the test result.  
1.2 Types of measurement scales used for expressing observations and test results are discussed.  
1.3 No system of units is specified in this standard.  
1.4 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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Standard Practice for Collection and Preservation of Information and Physical Items by a Technical Investigator

SIGNIFICANCE AND USE
2.1 This practice is intended for use by any technical investigator when investigating an incident that can be reasonably expected to be the subject of litigation. The intent is to obtain sufficient information and physical items to identify evidence associated with the incident and to preserve it for analysis.  
2.2 The quality of evidence may change with time, therefore, special effort should be taken to capture and preserve evidence in an expeditious manner. This practice sets forth guidelines for the collection and preservation of evidence for further analysis.  
2.3 Evidence that has been collected and preserved is identified with, and traceable to, the incident. This practice sets forth guidelines for such procedures.
SCOPE
1.1 This practice covers guidelines for the collection and preservation of information and physical items by any technical investigator pertaining to an incident that can be reasonably expected to be the subject of litigation.  
1.2 This practice describes generally accepted professional principles and operations, although the facts and issues of each situation require consideration, and frequently involve matters not expressly dealt with herein. Deviations from this practice should be based on specific articulable circumstances.  
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.4 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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Standard Practice for Determination of Soluble Residual Contaminants in Materials by Ultrasonic Extraction

SIGNIFICANCE AND USE
5.1 This practice is suitable for the determination of extractable substances that may be found in materials used in systems or components requiring a high level of cleanliness, such as oxygen systems. Soft goods, such as seals and valve seats, may be tested as received. Gloves and wipes, or samples thereof, to be used in cleaning operations may be evaluated prior to use to ensure that the proposed extracting agent does not extract or deposit chemicals, or both, on the surface to be cleaned.  
5.2 Wipes or other cleaning equipment may be tested after use to determine the amount of contaminant removed from a surface.
Note 1: The amount of material extracted may be dependent upon the frequency and power density of the ultrasonic unit.  
5.3 The extraction efficiency has been shown to vary with the frequency and power density of the ultrasonic unit. The unit, therefore, must be carefully evaluated to optimize the extraction conditions.
SCOPE
1.1 This practice may be used to extract nonvolatile and semivolatile residues from materials such as new and used gloves, new and used wipes, component soft goods, and so forth. When used with proposed cleaning materials (wipes, gloves, and so forth), this practice may be used to determine the potential of the proposed solvent or other fluids to extract contaminants (plasticizers, residual detergents, brighteners, and so forth) and deposit them on the surface being cleaned.  
1.2 This practice is not suitable for the evaluation of particulate contamination.  
1.3 The values stated in SI units are to be regarded standard. No other units of measurement are included in this standard.  
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Standard Practice for Determination of a Pooled Limit of Quantitation for a Test Method

SIGNIFICANCE AND USE
5.1 Background—In a single laboratory, the limit of quantitation, LOQ, equal to ten times the standard deviation obtained under repeatability conditions extrapolated to zero concentration (s0) based on samples with close to zero concentrations has been recommended.3 A test result at this LOQ has an uncertainty of ±30 % at the 99 % confidence level.  
5.1.1 This practice uses a regression technique to determine a similar limit for a test method (PLOQ) using statistically pooled repeatability standard deviations over multiple operators/laboratories/samples from ILS data. This PLOQ can be used by industry to assess the reliability of a test method, or, compare reliability of different test methods, for quantitative measurement at concentrations near zero. Similarly, quantitative test results obtained using the test method for levels at or below the PLOQ can be expected by industry to have an uncertainty of ±30 % or greater at the 95 % confidence level.  
5.1.2 The regression technique described in this practice can also be used to determine a limit of quantitation specific for a single laboratory (LLOQ). The limit thus quantified for one laboratory is defined by this standard as the laboratory limit of quantitation (LLOQ).  
5.1.3 It should be noted that since differences in repeatability testing capabilities between different laboratories can exist, therefore, LLOQ determined at a single laboratory can be different than the PLOQ determined for the test method.  
5.2 Values below the PLOQ are deemed by this practice to be too uncertain for meaningful use in commerce, or in regulatory activities.
SCOPE
1.1 This practice covers the use of standard regression techniques and data from an interlaboratory study to determine a lower quantitative limit for a test method. This determined lower limit represents the numerical limit at or above which the test results are considered to be quantitatively meaningful for commerce or regulatory activities by this practice. It is defined by this standard as the pooled limit of quantitation (PLOQ) for the test method.  
1.2 This practice is applicable to test methods that are capable of producing numerical test results close to zero. Examples are those test methods that determine quantitatively the concentration of analyte(s) near zero.  
1.3 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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ASTM
ASTM E691-23(Practice)
Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method

ABSTRACT
This practice describes the techniques for planning, conducting, analyzing, and treating the results of an interlaboratory study (ILS) of a test method. The statistical techniques described in this practice provide adequate information for formulating the precision statement of a test method. This practice is also concerned exclusively with test methods which yield a single numerical figure as the test result, although the single figure may be the outcome of a calculation from a set of measurements. ASTM regulations require precision statements in all test methods in terms of repeatability and reproducibility and knowledge of the test method precision is useful in commerce and in technical work when comparing test results against standard values or between data sources.
SIGNIFICANCE AND USE
4.1 ASTM regulations require precision statements in all test methods in terms of repeatability and reproducibility. This practice may be used in obtaining the needed information as simply as possible. This information may then be used to prepare a precision statement in accordance with Practice E177. Knowledge of the test method precision is useful in commerce and in technical work when comparing test results against standard values (such as specification limits) or between data sources (different laboratories, instruments, etc.).  
4.1.1 When a test method is applied to a large number of portions of a material that are as nearly alike as possible, the test results obtained will not all have the same value. A measure of the degree of agreement among these test results describes the precision of the test method for that material. Numerical measures of the variability between such test results provide inverse measures of the precision of the test method. Greater variability implies smaller (that is, poorer) precision and larger imprecision.  
4.1.2 Precision is reported as a standard deviation, coefficient of variation (relative standard deviation), variance, or a precision limit (a data range indicating no statistically significant difference between test results).  
4.1.3 This practice is designed only to estimate the precision of a test method. However, when accepted reference values are available for the property levels, the test result data obtained according to this practice may be used in estimating the bias of the test method. For a discussion of bias estimation and the relationships between precision, bias, and accuracy, see Practice E177.  
4.2 The procedures presented in this practice consist of three basic steps: planning the interlaboratory study, guiding the testing phase of the study, and analyzing the test result data.  
4.2.1 The planning phase includes forming the ILS task group, the study design, selection, and number of participating laborato...
SCOPE
1.1 This practice describes the techniques for planning, conducting, analyzing, and treating the results of an interlaboratory study (ILS) of a test method. The statistical techniques described in this practice provide adequate information for formulating the precision statement of a test method.  
1.2 This practice does not concern itself with the development of test methods but rather with gathering the information needed for a test method precision statement after the development stage has been successfully completed. The data obtained in the interlaboratory study may indicate, however, that further effort is needed to improve the test method.  
1.3 Since the primary purpose of this practice is the development of the information needed for a precision statement, the experimental design in this practice may not be optimum for evaluating materials, apparatus, or individual laboratories.  
1.4 Field of Application—This practice is concerned exclusively with test methods which yield a single numerical figure as the test result, although the single figure may be the outcome of a calculation from a set of measurements.  
1.4.1 This practice ...

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