BS 5350-E1-1976 Methods of test for adhesives - Sampling and analysis of test data - Guide to statistical analysis《粘合剂试验方法 第E1部分 试验数据取样和分析 统计分析指南》.pdf
《BS 5350-E1-1976 Methods of test for adhesives - Sampling and analysis of test data - Guide to statistical analysis《粘合剂试验方法 第E1部分 试验数据取样和分析 统计分析指南》.pdf》由会员分享,可在线阅读,更多相关《BS 5350-E1-1976 Methods of test for adhesives - Sampling and analysis of test data - Guide to statistical analysis《粘合剂试验方法 第E1部分 试验数据取样和分析 统计分析指南》.pdf(10页珍藏版)》请在麦多课文档分享上搜索。
1、BRITISH STANDARD CONFIRMED NOVEMBER 1983 BS 5350-E1: 1976 Incorporating Amendment No. 1 Methods of test for Adhesives Part E1: Guide to statistical analysis UDC 665.93:620.1:519.23BS5350-E1:1976 This British Standard, having been prepared under the authorityof the Adhesives Standards Committee, wasp
2、ublished under the authorityofthe Executive Boardon 30 November1976 BSI 07-1999 The following BSI references relate to work on this standard: Committee reference ADC/9/2 Draft for comment 74/50318 ISBN 0 580 09335 2 Foreword Physical testing invariably yields scattered results and simple attempts to
3、 obtain improved reliability in the estimate of the quantity under study involve replicate experiments. Tests on adhesives are particularly prone to scatter and it is therefore desirable to apply a rigorous statistical treatment to such test data so that an objective interpretation can be made. A Br
4、itish Standard does not purport to include all the necessary provisions of a contract. Users of British Standards are responsible for their correct application. Compliance with a British Standard does not of itself confer immunity from legal obligations. Summary of pages This document comprises a fr
5、ont cover, an inside front cover, pages i and ii, pages1 to 4 and a back cover. This standard has been updated (see copyright date) and may have had amendments incorporated. This will be indicated in the amendment table on theinside front cover. Amendments issued since publication Amd. No. Date of i
6、ssue Comments 6285 April 1990 Indicated by a sideline in the marginBS5350-E1:1976 BSI 07-1999 i Contents Page Foreword Inside front cover 1 Scope 1 2 Reference 1 3 Definitions 1 4 Use of arithmetic mean and standard deviation 1 5 Calculations 1 6 Confidence limits for the mean 1 7 Significance of di
7、fference between means 1 8 Estimate of number of observations required 2 Appendix A Specimen calculation 3 Appendix B Estimation of standard deviation from small numbers of test results 3 Appendix C Values of t for 95 % confidence limits 4 Appendix D Approximate number of observations related to obs
8、erved coefficient of variation and required range about the mean 4 Appendix E Effect of number of observations on the confidence interval 4ii blankBS5350-E1:1976 BSI 07-1999 1 1 Scope This Part of BS5350 describes statistical methods which are valid even if a small number of test results (fewer than
9、10) is available. More detailed information is given in BS2846. 2 Reference This Part makes reference to the following standards publication: BS2846, Guide to statistical interpretation of data. 3 Definitions For the purposes of this Part of this British Standard the following definitions apply. 3.1
10、 arithmetic mean ( ) of a series of n observations of x 1 , x 1 , x 2 , x 3x n , is the sum of all the values divided by their number, i.e. this quantity is also commonly known as the average 3.2 standard deviation and variance the standard deviation (s) is the positive square root of the variance (
11、s 2 ) which is a measure of the dispersion of the test results. For a series of n observations x 1 , x 2 , x 3 , . x nand an arithmetic mean, the variance is given by the following expression: 3.3 coefficient of variation (v) the standard deviation expressed as a percentage of the mean 4 Use of arit
12、hmetic mean and standard deviation The arithmetic mean in most cases gives the statistically best estimate of the true value of the quantity observed, i.e.the value it would have were all random errors eliminated. The scatter of the results is described by the standard deviation. It is assumed that
13、the errors follow Gaussian or normal distribution. 5 Calculations The calculation of means and standard deviations is straightforward but laborious and the use of a desk calculator is recommended. The equation for estimating the standard deviation can be written as: This form is particularly useful
14、when a desk calculator is available. A specimen calculation showing a recommended tabular layout is given inAppendix A. Alternatively, when the number of test results is small (between2 and10) a simplified formula is available which gives an approximate but reasonable estimate of the standard deviat
15、ion. Details of this method are given inAppendix B. 6 Confidence limits for the mean In general, the mean of a set of observations approaches the true value more closely as the number of observations is increased provided that there are no systematic errors. From any finite number of observations, h
16、owever, the true value cannot be determined exactly; thus, not only the mean of a particular set of observations but also the limits which have have a given probability of including the true value should be calculated. For many purposes the95% confidence limits are found convenient. These define a r
17、ange within which the true value will lie on95% of occasions when the calculation is used. 7 Significance of difference between means It is not always immediately obvious whether the difference between the means of two series of observations is significant (i.e.a real one). One test is that if eithe
18、r95% confidence limits of the difference between the means include zero then the means are not significantly different at a5% level of significance. x x v 100s x - =BS5350-E1:1976 2 BSI 07-1999 The confidence limits, L, of the difference between two means are given by the formula: where and are the
19、two means; n 1and n 2are the number of observations in each set; t is read from the table inAppendix C for (n 1+ n 2 1) observations; and s is defined by where S 1and S 2are the two standard deviations. Alternatively a statistic t can be calculated, defined by: and compared with the value of t as de
20、fined above. The difference between the means is significant ift 1 t, and is not significant if t 1u t, at the5% significance level. The method described is only valid if it can be assumed that the two series of observations come from populations with similar standard deviations, i.e.s 1and s 2are e
21、stimates of the same quantity. 8 Estimate of number of observations required If it is desired that the95% confidence interval of a mean shall lie within a predetermined range around the mean, then it is necessary first to determine the variance and then to calculate the number of observations that n
22、eed to be made. The table inAppendix D relates the approximate number of observations required in an isolated series of tests to the observed value of the coefficient of variation and to the required limits expressed as a percentage of the mean. Thus, if it is desired that the95% confidence limits s
23、hall lie within10% of the mean and if the coefficient of variation is20%, it will be necessary to take the mean of about18 observations. The figures inAppendix D, however, constitute a guide only, as variations in and s will occur in successive sets of observations. Hence the values of s and L for a
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