Why cables can be expensive

I ask you again. If you percieve a bit of kit (presumably NVA) sounds better than another, there must be some physical difference in the way the kit processes the input. What is that difference, then? Or could it all be in your head?

ALL the evidence points to the types of differences we are talking about being mostly psychological in nature.

Chris


Edited by Dev to remove personal comments.

 

Do you actually have any hi-fi, do you actually listen to music, or do you just play with your test gear?

You are basically just ** ********* **** ***, as you prove in the above post and as you have also proved in the past, so there is no point in trying to communicate with you.

For mods - you choose not to remove personal insults aimed at members so you condone and create this situation, you create the environment that these so called discussions occur in so you get the forum you create!!

 

Well there's the handbags gone, now watch out for the Jimmy Choos. We are definitely in a zero gain forum just now!

Please help, I'm not sure I understand you Mescalito; are you saying that you have NEVER heard a system sound different by swapping around cables, or that there are not consistent length related measurable electrical characteristics associated with different cables?


Back in the 70's you could have been straightjacketed for alleging that the construction of a small signal cap on a circuit board could influence the sound of an amp, let alone a poxy resistor or choke! Not a lot of us would argue for a double blind test on that any more. Yet the remainder of nominally 'passive' components - wires, pcb, rail materials, connectors and solder, etc, are still seen as being in some sense separate entities not important enough to influence the sound, rather than existing in an integrated continuum on the circuit board and contributing to the overall performance, however slight.

 

If you can point out the insults we'd be happy to remove them.

 

I would have thought it was pretty obvious.

Edited by Dev to remove quotes

Good moderation would have removed every post that contained ad hominem. There was a perfectly good discussion / argument going on about the subject. Then two people started to address the poster (namely me) with personal insults and personal criticism - that is ad hominem - it is unnecessary, and always creates an ad hominem reponse if not removed, so you have conflict. You removed the gross one from SQ but left the other. I would have thought you would have learned from the situation a couple of years ago with the likes of Stereo Mic when it nearly killed your forum. Don't make the same mistake.

Disagreement and discussion on a subject of a thread no matter how heated and opinionated is good stuff but as soon as you allow a poster to turn it personal and addressed to the poster instead of the subject you should remove those posts, otherwise the thread is always derailed.

 

Agreed, but

we cannot be expected to read every single post. That is why we ask posters to report any post that breaches the AUP and if we agree then we'll act.

 

There's those who believe that they can hear things that people cannot measure, and there are those who believe that everything you can hear can be measured and explained.

It really is that simple- those who believe they can hear things that cannot be measured can only perform this trick with the benefit of knowing which cable is playing by seeing the cable.

They may claim otherwise, but there has, as yet, been no third party verified examples of Blind A/B testing of cables where a tester has been able to identify any cable more than would be expected by chance.

Should someone make that claim then it's only fair to expect them to provide proof to back that claim up.

 

No, I place the cable between the components in the system and listen.
When it invariably sounds identical to the last cable tried I relax in the knowledge that the 'artists' have lost the plot.

Again you are acting the strawman.
Who's putting signals unrelated to those in normal use through the cable?
Where did you get that idea?
Even in the null tests I've proposed we do it with either digital signals in the case of a digital cable or analogue (music) if testing an analogue interconnect.

 

I agree, good strong argument is good.
You'll get no personal attack from me - can't be arsed with it these days - nor would I look to censor any argument you post.
Having said that, sometimes you simply have to aim a post at the poster and not just the subject, particularly where the poster has extremely strong opinions but it clearly shouldn't turn to insults or attacks on personal character.

But this forum is no better or worse than any other in that respect.
All forums other than those with Stalinist iron rod moderation suffer to the same degree.

I suspect that if a few personal posts have sat around unmoderated for a while it's because, like me the other mods have been busy watching Midsomer Murders or the footy

 

I think you are avoiding an obvious conclusion, either *you* cannot hear it, or *your* system doesn't resolve that level of information.

I can show anyone who wishes, in my system, two cables that look externally the same, have the same plugs, measure the same, but sound musically different, one being clearly superior. You wont know which is which by handling or looking at them so there will be no psychology involved. I have done it with many people and customers who own both types have done it themselves with the same consistency. Go to The Hi-Fi Subjectivist and ask the guys there who have done it.

On the other subject you obviously don't know what null means if you think it is just connecting it to your system. A null test is done with a frequency sweep.

 

The Hi-Fi Subjectivist doesn't suffer from it because as soon as someone addresses the poster individually as part of the argument the post is removed - so there is *no* conflict. You get regular bouts or conflict still on Zerogain but at least it is leagues better than it used to be, as someone obviously saw some common sense as it was killing your forum.

It is still in the archive for all to see, it was a plague.

 

You still don't seem to accept that I've used lots of different kit and many, many pairs of ears to form my opinions. If I'd simply stuck to the same kit and listened alone for years I agree you might have a point.

As for the null - again I disagree.
We did this recently with CD lathing.
Play a lathed CD and record the digital output.
Play a standard CD and make an identical recording - change absolutely nothing.
Now invert phase on one recording and combine.
Absolutely flat line and zero audio output is a null, anything else isn't.
For verification you can play back the recording and admire the total silence.

I've looked at Subjectivist but I'm afraid it is the very embodiment of all that is wrong with audio IMO. I stress IMO - others will enjoy that approach but it simply doesn't appeal to me.

 

Quite simply - gobble-de-gook breeds gobble-de-gook. Here is a classic example, on subject if tangental.

Null hypothesis
For the periodical, see Null Hypothesis: The Journal of Unlikely Science.
Main article: Statistical hypothesis testing

The practice of science involves formulating and testing hypotheses, assertions that are falsifiable using a test of observed data. The null hypothesis, typically proposes a general or default position, such as that there is no relationship between two measured phenomena, or that a potential treatment has no effect. The term was originally coined by English geneticist and statistician Ronald Fisher. It is typically paired with a second hypothesis, the alternative hypothesis, which asserts a particular relationship between the phenomena. Jerzy Neyman and Egon Pearson formalized the notion of the alternative. The alternative need not be the logical negation of the null hypothesis and is the predicted hypothesis you would get from the experiment. The use of alternative hypotheses was not part of Fisher's formulation, but became standard.

Hypothesis testing works by collecting data and measuring how probable the data is, assuming the null hypothesis is true. If the data is very improbable (usually defined as observed less than 5% of the time), then the experimenter concludes that the null hypothesis is false. If the data do not contradict the null hypothesis, then no conclusion is made. In this case, the null hypothesis could be true or false; the data gives insufficient evidence to make any conclusion.

For instance, a certain drug may reduce the chance of having a heart attack. Possible null hypotheses are "this drug does not reduce the chances of having a heart attack" and "this drug has no effect on the chances of having a heart attack". The test of the hypothesis consists of administering the drug to half of the people in a study group as a controlled experiment. If the data show a statistically significant change in the people receiving the drug, the null hypothesis is rejected.

The choice of null hypothesis is critical. Consider the question of whether a tossed coin is fair (i.e. that on average it lands heads up 50% of the time). A potential null hypothesis is "this coin is not biased towards heads". The experiment is to repeatedly toss the coin. A possible result of 5 tosses is 5 heads. Under this null hypothesis, the data are considered unlikely (with a fair coin, the probability of this is 3%). The data refutes the null hypothesis: the coin is biased.

Alternatively, the null hypothesis, "this coin is fair" allows runs of tails as well as heads, increasing the probability of 5 of a kind to 6%, which is no longer statistically significant, preserving the null hypothesis.

This example illustrates one hazard of hypothesis testing: evaluating a large number of true null hypotheses against a single dataset is likely to spuriously reject some of them because of the inevitable noise in the data. However, formulating the null hypothesis before collecting data, rejects a true null hypothesis only a small percent of the time.

Testing for differences
In scientific and medical research, null hypotheses play a major role in testing the significance of differences in treatment and control groups. This use, while widespread, offers several grounds for criticism, including straw man, Bayesian criticism and publication bias.

The typical null hypothesis at the outset of the experiment is that no difference exists between the control and experimental groups (for the variable being compared). Other possibilities include:

that values in samples from a given population can be modeled using a certain family of statistical distributions.
that the variability of data in different groups is the same, although they may be centered around different values.

Example
Given the test scores of two random samples of men and women, does one group differ from the other? A possible null hypothesis is that the mean male score is the same as the mean female score:

H0:μ1 = μ2
where:

H0 = the null hypothesis
μ1 = the mean of population 1, and
μ2 = the mean of population 2.
A stronger null hypothesis is that the two samples are drawn from the same population, such that the variance and shape of the distributions are also equal.

Directionality
Quite often statements of null hypotheses appear not to have a "directionality", namely, that values are identical. However, null hypotheses can and do have "direction"â€â€in many instances statistical theory allows the formulation of the test procedure to be simplified, thus the test is equivalent to testing for an exact identity. For instance, when formulating a one-tailed alternative hypothesis, application of Drug A will lead to increased growth in patients, then the true null hypothesis is the opposite of the alternative hypothesis i.e. application of Drug A will not lead to increased growth in patients. The effective null hypothesis will be application of Drug A will have no effect on growth in patients.

In order to understand why the effective null hypothesis is valid, it is instructive to consider the above hypotheses. The alternative predicts that exposed patients exposed experience increased growth compared to the control group. That is,

H1:μdrug > μcontrol
where:
μ = the patients' mean growth.
The effective null hypothesis is H0:μdrug = μcontrol .

The true null hypothesis is.
The reduction occurs because, in order to gauge support for the alternative, classical hypothesis testing requires calculating how often the results would be as or more extreme than the observations. This requires measuring the probability of rejecting the null hypothesis for each possibility it includes and second to ensure that these probabilities are all less than or equal to the test's quoted significance level. For reasonable test procedures the largest such probability occurs on the region boundary HT, specifically for the cases included in H0 only. Thus the test procedure can be defined (that is the critical values can be defined) for testing the null hypothesis HT exactly as if the null hypothesis of interest was the reduced version H0.

Fisher said, "the null hypothesis must be exact, that is free of vagueness and ambiguity, because it must supply the basis of the 'problem of distribution,' of which the test of significance is the solution", implying a more restrictive domain for H0. According to this view, the null hypothesis must be numerically exactâ€â€it must state that a particular quantity or difference is equal to a particular number. In classical science, it is most typically the statement that there is no effect of a particular treatment; in observations, it is typically that there is no difference between the value of a particular measured variable and that of a prediction. The majority of null hypotheses in practice do not meet this "exactness"criterion. For example, consider the usual test that two means are equal where the true values of the variances are unknownâ€â€exact values of the variances are not specified.

Most statisticians believe that it is valid to state direction as a part of null hypothesis, or as part of a null hypothesis/alternative hypothesis pair.[6] The logic is quite simple: if the direction is omitted, then if the null hypothesis is not rejected it is quite confusing to interpret the conclusion. For example, consider an H0 that claims the population mean = 10, with the one-tailed alternative mean > 10. If the sample evidence obtained through x-bar equals −200 and the corresponding t-test statistic equals −50, what is the conclusion? Not enough evidence to reject the null hypothesis? Surely not! But we cannot accept the one-sided alternative in this case. Therefore, to overcome this ambiguity, it is better to include the direction of the effect if the test is one-sided. The statistical theory required to deal with the simple cases dealt with here, and more complicated ones, makes use of the concept of an unbiased test.

Sample size
Statistical hypothesis testing involves performing the same experiment on multiple subjects. The number of subjects is known as the sample size. The procedure depends on the size. Even if a null hypothesis does not hold for the population, an insufficient sample size may prevent its rejection. Minimum sample size depends on the statistical power of the test, the effect size that the test must reveal and the desired significance level. The significance level is the probability of rejecting the null hypothesis when the null hypothesis holds in the population. The statistical power is the probability of rejecting the null hypothesis when it does not hold in the population (i.e., for a particular effect size).

 

It can be a very fine line at times and again I think it comes back to the strength of opinion expressed. You rarely get unpleasant conflict where strong opinions are absent but then things can also get a bit dull. I prefer people not to sit on the fence and be open, even if the argument ruffles feathers though it shouldn't move to personal character attack.

Sometimes of course the poster is the subject and you cannot divorce them.
For example, a discussion around say Peter Walker's listening and testing methods inevitably turns to a discussion about him, because to many he embodied a certain type of thinking. That naturally gets the blood flowing sometimes.

 

Quite simply the null test in this senario is you are incapable of hearing it - as you don't hear it - QED

 

So why does the graphical representation of the signal show a flat line - a complete bit perfect cancelation?

A flat line is flat line.

The recording contains no data other than residual noise from the recording at sub -100db.

Nobody can hear what evidently does not exist.

 

At last you get the point - *he* is the subject not the poster. Anyone can discuss me and insult me all they want if I am the subject of the thread, that is not ad hominem. But if the poster on the thread about me is attacked personally for his opinions about me then that is ad hominem.

So if you wish to host that sort of thing then create a thread with the title, for example, Richard Dunn is a twonk - discuss! But it will just get silly as there will be retaliatory threads started and the forum will really sink into the mud.

 

It isn't always so clear cut.
Threads wander all over the place and will often move from discussion of the subject to the poster.

People just need to be adult at the end of the day and moderators need to exercise common sense.

 

Quite simply a flat line has been created by a piece of metal with components in it that is measuring and trying to null, in some cases, another piece of metal with components in it. You presume that the test is as subtle or revealing as the human ear and the conscious energetic perceptive nature of humanity, obviously it is not. It would be like using a hydrometer to null two wines and that will tell you how they will taste, just as big a waste of time.

The thing that makes me laugh is the arrogance involved in all this, that we presume to understand and can give specs and measure the way the human system reacts to musical stimulation by using a box with components and wires in it. Plain bloody daft.

That box has a purpose, but it is very simple purpose, it tells you simple unsubtle things in the development of circuits and in the testing and repair of existing equipment, it quite simply cannot tell you what is good music, only the human ear and energetic system can do that. AND that will have more than a small degree of individuality involved in those choices, and that is what makes this hobby so interesting, from your view point it is all a boring waste of time.

 

Because a graphical representation is not music.