What do you consider a sample to mean during an EICR

There is an assumption about the independence or not of the installation events - so if you know that each socket in a room was fitted by a different team member then finding one bad one tells you very little about the others. The events are about as independent as they could be.

If however you know they were done by the same chap on the same day, then if he has used wood screws and pasta instead of the proper bolts, and earth sleeving on one, then it is likely he has on the others too - there is a correlation. Equally if one or two are neat and tidy ,they probably all are.

In reality sampling theory is all very well  but the rules that apply to yields and tolerances on parts made on the same machine in the same factory are not anything like as reliable applied to the case of wiring installed and then added to by persons unknown, perhaps in many phases with different workers and different levels of pressure to rush it on the cheap or to do a good job.

So how to estimate the correlation ?- well if there has been an obvious new extension, that was probably all done at once, especially if all the switches are the same pattern and the sockets are all the same style, but rooms with a mix of styles of fittings and heights indicate poor correlation.

New does not mean better or worse but perhaps it does mean you only need to sample a few if they look well correlated.

The problem is the need for having seen a few of each kind to know which category it should go in. 

I agree with the dismantling can damage as much as it prevents in some cases -  so an earth test to the exposed screws or the earth pin may be not only faster but safer than a full tear down and R1 + R2, also a global L+N to E insulation at 250V may save the embarrassment of killing some prize item not isolated, and still finds 99% of real cable damage etc that a 500V wire by wire test would have .  Casting a wider net of looser tests, and a very good look and sniff will probably find more than a smaller  percentage of total dismantling.

mike

mapj1 said:

If however you know they were done by the same chap on the same day, then if he has used wood screws and pasta instead of the proper bolts, and earth sleeving on one, then it is likely he has on the others too - there is a correlation. Equally if one or two are neat and tidy ,they probably all are.

This is a load of rubbish, if you consider a dwelling (which we know usually falls outside the "sampling theory" statistics) may have been tampered with by anyone following installation - including DIY.

mapj1 said:

There is an assumption about the independence or not of the installation events - so if you know that each socket in a room was fitted by a different team member then finding one bad one tells you very little about the others. The events are about as independent as they could be.

Yes, that is exactly why the "sampling theorem" is important.

mapj1 said:

In reality sampling theory is all very well  but the rules that apply to yields and tolerances on parts made on the same machine in the same factory are not anything like as reliable applied to the case of wiring installed and then added to by persons unknown, perhaps in many phases with different workers and different levels of pressure to rush it on the cheap or to do a good job.

But I think in many installations, we are in the position of the latter case?

mapj1 said:

So how to estimate the correlation ?- well if there has been an obvious new extension, that was probably all done at once, especially if all the switches are the same pattern and the sockets are all the same style, but rooms with a mix of styles of fittings and heights indicate poor correlation.

That is based on the assumption that it was all OK on "day 1", and I agree it's not that simple .. but the statistics won't help here one way or the other.

gkenyon said:

mapj1 said:

If however you know they were done by the same chap on the same day, then if he has used wood screws and pasta instead of the proper bolts, and earth sleeving on one, then it is likely he has on the others too - there is a correlation. Equally if one or two are neat and tidy ,they probably all are.

This is a load of rubbish, if you consider a dwelling (which we know usually falls outside the "sampling theory" statistics) may have been tampered with by anyone following installation - including DIY.

Well, if you toss a coin 6 times and it comes up heads each time, you might want to turn it over to see whether it is a proper coin (1.5% chance) or a two-headed one.

If it is a genuine one, then of course the chance of heads next time is 50%; but even then we cannot be sure because the way the coin is tossed may be biased.

In practical terms, I tend to agree with Mike. If all of the workmanship that you have inspected is good, it is likely that the rest will be and based upon your population and sample sizes, one can calculate the degree of confidence. Then of course, you have to decide whether balance of probabilities is good enough, or do you want to be beyond reasonable doubt?

gkenyon said:

mapj1 said:

If however you know they were done by the same chap on the same day, then if he has used wood screws and pasta instead of the proper bolts, and earth sleeving on one, then it is likely he has on the others too - there is a correlation. Equally if one or two are neat and tidy ,they probably all are.

This is a load of rubbish, if you consider a dwelling (which we know usually falls outside the "sampling theory" statistics) may have been tampered with by anyone following installation - including DIY.

Well, if you toss a coin 6 times and it comes up heads each time, you might want to turn it over to see whether it is a proper coin (1.5% chance) or a two-headed one.

If it is a genuine one, then of course the chance of heads next time is 50%; but even then we cannot be sure because the way the coin is tossed may be biased.

In practical terms, I tend to agree with Mike. If all of the workmanship that you have inspected is good, it is likely that the rest will be and based upon your population and sample sizes, one can calculate the degree of confidence. Then of course, you have to decide whether balance of probabilities is good enough, or do you want to be beyond reasonable doubt?