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More than 85% INDIANS back BJP over Aamir Khan : Times of India

This is a much better line to take with disputing the result than the "22,000" is too tiny a sample for 1.25 billion people etc etc.

I mean we all know just how bad exit polls have often been too, and not just in India.

Discrepancies ultimately come from non-random factors like bias.

But that is a very deep and immense argument/debate by itself.

After all the bhakts will say that non-bhakts also rally to influence polls etc....and that was the ultimate reason when something does not go their way.

Who is to know for sure ultimately? Not me or you.
it is purely laughable that someone claiming to have done a PhD thinks that 0.01% of a population can miraculously cover the whole 1.25 billion population....if that was the case every scientific mistake would have been accepted instead of being discredited as statistically insignificant!!

Seriously make use of your education dont behave as a troll!

wont work only when its against RSS
you tell me....IF I blindfold myself and point at an indian from 1.25 billion what is the chance I find a say Christian (I think the population is higher than 0.01%)? or one with real Portuguese ancestry (something closer to 0.01%) in say Tamil Nadu or Kashmir?

@Nilgiri @deckingraj for future reference, you will have better luck explaining to a rock anything intelligent. Sampling principles, unfortunately will fail.

I almost fell off my chair at 1%
Seriously some of you have foreign flags and know not even the basics....or pretend to be smarter than people who actually have a degree in such a field :tsk:

Sometimes I do feel a rock would be more reasonable than an indian I wont even say indian troll coz as per your logic since I have seen enough indian trolls it can be safely equated to all indians are tolls :agree:

Again you have not picked up a statistics book and understand how normal distribution works even for a simple binomial system. There is a magic number of 30 (I won't go into the reasons why - because you have so far not bothered to counter anything with actual statistical reasoning) that as long as you are higher than (in your sample size), you have the start of statistical significance as long as it is totally random selection....no matter how big the population is.

If we had 30 samples instead of 22,000 for example for this response, the 95% confidence interval still has bounds of 72% and 98% (with center at 85%). The question again becomes the randomness of the sample (and thus its bias)....not its size.

This may be a helpful resource for you if you want to get grounded on some very basic things and concepts regarding population analysis through sampling, because you seem to know absolutely nothing on this matter:

Sampling Distributions
No I am not Jana...

and yes that would be interesting but where was the survey taken? Online...

How many people of india have access to internet and spend time doing online survey?
How many answer it properly and not to troll?
How many say what they really feel or arent ashamed to feel like a black sheep?

Lastly, who processed the survey? were they politically motivated?

What example?? A sample size of 22K is good for you or not?? Contradict or acknowledge that it is a good enough sample size...see how debates can be made simple...
I say it is questionable
 
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it is purely laughable that someone claiming to have done a PhD thinks that 0.01% of a population can miraculously cover the whole 1.25 billion population....if that was the case every scientific mistake would have been accepted instead of being discredited as statistically insignificant!!

Seriously make use of your education dont behave as a troll!

Ok I see you do speak with the a self-professed conviction of some religious fundamentalist....just like people have said about you in this thread already.

No matter how much Science or rationale reasoning we give you, you will always resort to the bare line of faith trumping it all. The "nyaah nyaaaah you are wrong no matter what!"

Again I direct you to read at the very least:

Sampling Distributions

and then bring up specific points if there is something you don't understand.

But it seems you are too lazy, unwilling or just outright unintelligent to do so before opening your mouth and continuing your braying.

Any reasonably intelligent person reading this thread will easily see who is being the troll here.

Seriously some of you have foreign flags and know not even the basics....or pretend to be smarter than people who actually have a degree in such a field

LOL this gets even better. You are claiming you have a degree in this field? You are the one avoiding the basics at very elementary statistical explanations like the one provided earlier. Central limit theorem, normal distribution, confidence intervals and limits, standard error, bias, estimators....it is quite clear these are all very alien concepts since you have not once brought any of them up yourself, or established any debate on them....since it is clear you know nothing about them.

Instead you completely skirt the very fundamental definition of what a normal distribution is, what happens to all distributions at sample size>30 and the very basis of the central limit theorem....and instead jump right to sample ratio % and probability which have next to nothing to do with normal distributions in the context of sample sizes and confidence levels in the context we are talking about.

The very basic reason is similar to flipping a coin. Say you flip a coin 10 times and write down the number of heads.

Then you do this process 100 times ( a total of 1000 flips) and each time you write down the number of heads. So your sample size is 100. You will find this is normally distributed.

Now if you do this process 1000 times(total of 10,000 flips), your normal distribution does not become 10 times more statistically significant or better...since we have already established the randomness of an essentially binomial coin flip. It will get a somewhat better precision and confidence interval resolution, thats about it. In fact I can show you the exact calculation to prove this, but you first have to respond with some modicum of understanding and intelligence on this subject, which you have thus far failed to do.

Now lets say someone secretly weights the coin to an unknown degree and you dont know this weight (basically the coin is no longer 50/50 fair but you dont know the exact level and need to flip to test it)....dont you think it would be silly to flip it millions of times when you will probably see the result much earlier on? You will see it both in the sheer binomial distribution and normal distribution too (if you decide to structure it that way like described earlier).....because essentially it is still a perfectly random process (coin flipping) for all intents and purposes....even if the coin itself is weighted.

It is only that randomness that can thus come into question when we are talking about the relevance of a sample to its larger population as long as the sample itself is more than 30 (a rule of thumb since this is when many various distributions converge in various parameters - and their sample distributions show normal distribution)

If you know of some Pakistani member on this forum that actually has a background in statistics, please ask him/her to continue this debate on your behalf....they may actually bring some points that matter from a fundamentally solid position w.r.t statistical analysis. It is pointless to have you humiliated further. I will not waste any more time trying to explain basic things to you since you are quite obviously not from this background and are making no attempt to actually learn some basics to debate constructively. Anyone else that reads this is free to engage with me on whatever point of interest.

No I am not Jana...

Yeah obviously! It is quite clear now. She definitely would not engage in this level of nonsense in a field she has no idea or inkling about.

and yes that would be interesting but where was the survey taken? Online...

Good now we are getting somewhere (just a little). You finally dont attack it on the basis of its sample size (which made you look really dumb...and dumber when you stuck to it - though it seems you still havent abandoned that line of reasoning).

Yes having the survey online will present a bias, since we cannot assume it is a perfect random sample anymore. The extent will of course need further analysis and study, but who is going to really care about doing that? The topic itself is quite an insignificant one to conduct such a time consuming and empirical analysis for.

Quick response online surveys are the best bet for these kinds of questions....those who want to believe in the results will do so....those who wont....will not. Increasing the randomness (and therefore data acquisition cost) is simply not a good return on investment for this case.

How many people of india have access to internet and spend time doing online survey?

You will have to do a representative study on that topic alone. For now it can only be labelled as a source of bias. We have no correction coefficient data to employ to account for it.

How many answer it properly and not to troll?

Its a yes or no answer. How does one troll a binomial selection?

How many say what they really feel or arent ashamed to feel like a black sheep?

Their identities are made known to everyone after they poll? Or this is an anonymous poll? Do you have any idea how dumb you sound right now?

Lastly, who processed the survey? were they politically motivated?

So even if the sample size was to your liking (lets say hundred of millions), you will still pull out this desperate last resort if the result is not to your liking. Glad no one cared enough to pre-emptively assuage a minority that cannot accept it is the minority....and their concerned brethren across the border:lol:....because they will just say "it was politically motivated" and "controlled" in the end....no matter how much is done to try satisfy their "concerns".
 
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Ok I see you do speak with the a self-professed conviction of some religious fundamentalist....just like people have said about you in this thread already.
So indians believe on hearsay....Explains the lynching and false accusation :agree:

Really? Just coz you said it, it becomes science? :o:

But it seems you are too lazy, unwilling or just outright unintelligent to do so before opening your mouth and continuing your braying.
Assumptions

Any reasonably intelligent person reading this thread will easily see who is being the troll here.
:enjoy:

You are claiming you have a degree in this field?
knowledge never proclaimed about degree but you did about your PhD or something...

it is quite clear these are all very alien concepts since you have not once brought any of them up yourself, or established any debate on them....since it is clear you know nothing about them.
I hated statistics but I do work with it but in a different field and we dont use tiny sample sizes....

LOL this gets even better. You are claiming you have a degree in this field? You are the one avoiding the basics at very elementary statistical explanations like the one provided earlier. Central limit theorem, normal distribution, confidence intervals and limits, standard error, bias, estimators....it is quite clear these are all very alien concepts since you have not once brought any of them up yourself, or established any debate on them....since it is clear you know nothing about them.

Instead you completely skirt the very fundamental definition of what a normal distribution is, what happens to all distributions at sample size>30 and the very basis of the central limit theorem....and instead jump right to sample ratio % and probability which have next to nothing to do with normal distributions in the context of sample sizes and confidence levels in the context we are talking about.

The very basic reason is similar to flipping a coin. Say you flip a coin 10 times and write down the number of heads.

Then you do this process 100 times ( a total of 1000 flips) and each time you write down the number of heads. So your sample size is 100. You will find this is normally distributed.

Now if you do this process 1000 times(total of 10,000 flips), your normal distribution does not become 10 times more statistically significant or better...since we have already established the randomness of an essentially binomial coin flip. It will get a somewhat better precision and confidence interval resolution, thats about it. In fact I can show you the exact calculation to prove this, but you first have to respond with some modicum of understanding and intelligence on this subject, which you have thus far failed to do.

Now lets say someone secretly weights the coin to an unknown degree and you dont know this weight (basically the coin is no longer 50/50 fair but you dont know the exact level and need to flip to test it)....dont you think it would be silly to flip it millions of times when you will probably see the result much earlier on? You will see it both in the sheer binomial distribution and normal distribution too (if you decide to structure it that way like described earlier).....because essentially it is still a perfectly random process (coin flipping) for all intents and purposes....even if the coin itself is weighted.

It is only that randomness that can thus come into question when we are talking about the relevance of a sample to its larger population as long as the sample itself is more than 30 (a rule of thumb since this is when many various distributions converge in various parameters - and their sample distributions show normal distribution)

If you know of some Pakistani member on this forum that actually has a background in statistics, please ask him/her to continue this debate on your behalf....they may actually bring some points that matter from a fundamentally solid position w.r.t statistical analysis. It is pointless to have you humiliated further. I will not waste any more time trying to explain basic things to you since you are quite obviously not from this background and are making no attempt to actually learn some basics to debate constructively. Anyone else that reads this is free to engage with me on whatever point of interest.
I didnt read all this....too much wordings ...However, I did like how you assumed everything is normally distributed :enjoy: Maybe indians are less diverse than I thought
What you said is not very possible in human dynamics esp in large samples....sure Statisticians can produce any type of meaning from data provided to them....Run different tests on them....

You finally dont attack it on the basis of its sample size (which made you look really dumb...and dumber when you stuck to it - though it seems you still havent abandoned that line of reasoning).

Yes having the survey online will present a bias, since we cannot assume it is a perfect random sample anymore. The extent will of course need further analysis and study, but who is going to really care about doing that? The topic itself is quite an insignificant one to conduct such a time consuming and empirical analysis for.

Quick response online surveys are the best bet for these kinds of questions....those who want to believe in the results will do so....those who wont....will not. Increasing the randomness (and therefore data acquisition cost) is simply not a good return on investment for this case.
there is nothing dumb to assume there are more people with difference in opinion who dont have interest in dividing india into AK vs BJP
 
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Really? Just coz you said it, it becomes science? :o:

I invite you to pick up and read a statistics book and find something that contradicts anything that I said.

I hated statistics but I do work with it but in a different field and we dont use tiny sample sizes....

Explain please. What are your sample sizes , populations and assumed distributions.

I didnt read all this....too much wordings ...However, I did like how you assumed everything is normally distributed

Its ok, someone that is actually interested may read it and pose some questions and insight to it.

As for everything being normally distributed. You must first read up on the central limit theorem and its effect on other distributions once the sample size is larger than 30 or in case of binomial, that np > 5 and understand the significance of this. The proofs for these rule of thumbs are probably beyond your scope since just the coin flipping example bored you already.

But yes the normal distribution is one of those recurring universal truths, similar to euler number and pi, in the sheer massive frequency it appears with. Other distributions (which make a tiny tiny fraction) are themselves almost always variants of normal distribution given we are always talking about sample sizes larger than 30.

What you said is not very possible in human dynamics esp in large samples..

I know what you are trying to get at. But this is a simple yes/no and thus binomial system. The degrees of freedom (and thus error) are thus mitigated substantially. Again sample bias is really the only recourse of argument you have here.

sure Statisticians can produce any type of meaning from data provided to them....Run different tests on them....

A binomial problem? Not so much. Again the degrees of freedom are severely restricted in such a simple survey....it lowers error like I said....and it also lowers the options for statistical trickery. When you make the survey more complex, lets say instead of asking yes/no....the question asks you to rate the level of agreement in 5 separate possible answers (e.g strongly agree, agree, neutral, disagree, strongly disagree) then this will give way more leeway for a statistician to start using tricks to promote a particular agenda. Even this is actually quite hard to do in reality (but still much easier than say binomial)....but the variable response options and complexity have to be much more higher for what you are trying to describe to come into play....trust me I have run monte-carlo simulations with extremely high sensitivity coefficients - in essence we have to use a super computer to run the complete analysis many billions of times to get any useful data because of the statistical problems inherent within the physical model. But that is as far away from binomial modelling as you can get....it is multiple chains of varying complexity run in series.

there is nothing dumb to assume there are more people with difference in opinion who dont have interest in dividing india into AK vs BJP

I am saying from a purely sample size standpoint, your argument does not hold.

A moral assumption/qualifier like the one you are positing here is outside the realms of statistics and Science in general....since it is quite subjective and biased to begin with.
 
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I invite you to pick up and read a statistics book and find something that contradicts anything that I said.
I never said you contradict stats

I have my set of questions which still have gone unanswered :enjoy:
 
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I have my set of questions which still have gone unanswered :enjoy:

And what are those exactly? Or are you going to simply start with "sample size is less than 0.01%" again?

You sound like my significant other :D
 
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And what are those exactly? Or are you going to simply start with "sample size is less than 0.01%" again?

You sound like my significant other :D
I asked a few questions....

From where the samples were taken, what % do they represent?
How was the analysis done? Where they politically biased?
Who took part? Age group?
How did they filter out those with repeated accounts? or those with clicking habits?

OK but just some numbers regarding these will suffice. No need to qualify or say what they represent.
I deal with population size in thousands but that is to determine genes (in thousands) across genomes (sizes vary) using statistical probabilities (assuming the population normalized) Mostly parametric tests
 
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