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ISO 2602:1980 PDF — Statistical interpretation of test results — Estimation of the mean —… — GOST Standards

//ISO 2602:1980

ISO 2602:1980

Name: ISO 2602:1980 — Statistical interpretation of test results — Estimation of the mean — Confidence interval
SKU: ISO 2602:1980
Price: 25 EUR
Availability: InStock

Statistical interpretation of test results — Estimation of the mean — Confidence interval

Название (английский):

ISO 2602:1980

Statistical interpretation of test results — Estimation of the mean — Confidence interval

Статус документа:: Действующий
Формат:: Электронный (PDF)
Количество страниц:: 5
Дата публикации:: 1 февраля 1980 г.
Издание:: ISO IS 2602 edition 1 version 1
ICS:: 03.120.30

Тип поставки:

Full version25 €Ask AI2 €Read online 24h10 €Read online 72h15 €

Язык документа:

ruen

Срок поставки:1 рабочий день

Цена:25 €

Описание (английский):

Concerns the estimation of the mean of a normal population on the basis of a series of tests applied to a random sample of individuals drawn from this population when the variance of the population is unknown and calculation of the conficence interval for the population mean therefrom and from the standard deviation. Test method may be subject to systematic errors.

Abstract

Overview

Key Topics

Statistical Estimation of the Mean: Provides guidelines for estimating the mean value of a normal distribution using test results from a random sample.
Unknown Variance: Focuses on cases where the variance of the underlying population is unknown-a common scenario in laboratory and field testing.
Confidence Interval Calculation: Details procedures for calculating both two-sided and one-sided confidence intervals at 95% and 99% confidence levels, using the sample mean and standard deviation.
Large and Small Sample Methods: Explains calculation methods for both grouped and ungrouped results, including the use of the sample range for small sample sizes (n ≤ 12).
Test Result Handling: Stresses the importance of not discarding or correcting outlying results unless justified by clear technical or experimental reasons, ensuring valid statistical treatment.
Systematic Errors: Notes that systematic errors (bias) in test methods can affect results and are not accounted for in this standard; users must ensure the absence or identification of such biases for valid application.

Applications

ISO 2602:1980 is widely applicable in industries and research fields where statistical analysis of measurement data is required, including:

Quality Control: Used by manufacturers and testing laboratories to estimate population means from sample data, such as mean dimensions, strength, or purity of products.
Scientific Research: Supports researchers in designing experiments, interpreting data, and reporting mean values with appropriate confidence intervals.
Standards Compliance: Assists organizations in meeting regulatory and industry requirements for statistical evaluation of product or material properties.
Process Improvement: Enables process engineers and quality analysts to assess sample results, identify process capability, and drive improvements through informed decision-making.
Sampling and Testing Protocols: Useful in developing sampling plans, evaluating data from destructive and non-destructive tests, and ensuring reliable reporting of analytical results.

Related Standards

For comprehensive statistical analysis and terminology, the following ISO standards are referenced or recommended alongside ISO 2602:1980:

ISO 2854: Statistical treatment of data - Problems of estimation and tests of means and variances. Expands on estimation of means, variances, and hypothesis testing.
ISO 3534: Statistics - Vocabulary and symbols. Provides definitions and standardized symbols for statistical concepts and calculations.

These related standards help organizations develop an integrated approach to statistical interpretation and reporting, enhancing the reliability and comparability of test results.

Keywords: ISO 2602, estimation of the mean, confidence interval, statistical interpretation, unknown variance, normal population, sample mean, statistical analysis, quality control, laboratory testing, international standard.