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The null hypothesis. A skeptics best friend and worst enemy.

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posted on Mar, 30 2010 @ 12:16 AM
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I am writing this thread to help all of the skeptics at ATS who are inundated with MSM propaganda fed through a putrid public education system.
Some basic rules of "debuking":

The best friend, or worst enemy, at ATS is something that should urgently be grokked by all.
And this great accomplishment of Science is known as...
The Null Hypothesis.

The reason this has such power is that it forces the debunking trollers to see that logic does not, and will not prove a negative.

First let me say that I debunk things often, but with facts.
Facts are not personal folks.
Don't swell up your animal self in denial. LEARN.
Listen and Think my fellow Trogs.
Example:

It is not theoretically possible to "prove" that aliens do not exist. They are not integral in the closed system of observation used for this example.
(Btw.. How can you prove NOTHING?)

WARNING DEBUNKING DOGMA AHEAD!!

All that we know is surrounded by what we do not know, unless you are a lonely Solipsist.


This is the argument of ignorance. that promotes this crap.

The best one can do is establish the null hypothesis.
For something to be invalid, then evidence has to prove the validity of its opposite.
PROVE IT.

So instead of saying that aliens are not real. We try to prove that aliens are real.
By all of our methods of modern science, we cannot prove that alien life is empirically "real", but that is because the data is limited to our knowledge.

We cannot base a conclusion on the apparent absence of evidence.
According to the null hypothesis we have to prove something valid that makes it impossible for valid alien life.

And if we cannot, then their existence is UNKNOWN. DUH!

The only way a negative can invalidate a positive is in a CLOSED system where all facets are completely understood.

That means ALL THE FACETS, and not our limited understanding of some on it.
Simply because we cannot measure something does not mean that it is invalid.

Was gravity invalid before Newton?

What about AC power before Tesla?

What about the earth being flat or the center of everything?

What about Artificial Intelligence before algorithms?

Let's look at the null hypothesis:


A null hypothesis is a hypothesis (within the frequent context of statistical hypothesis testing) that might be falsified using a test of observed data. Such a test works by formulating a null hypothesis, collecting data, and calculating a measure of how probable those data were assuming the null hypothesis were true. If the data appear very improbable (usually defined as a type of data that should be observed less than 5% of the time) then the experimenter concludes that the null hypothesis is false. If the data look reasonable under the null hypothesis, then no conclusion is made. In this case, the null hypothesis could be true, or it could still be false; the data give insufficient evidence to make any conclusion.
The null hypothesis typically proposes a general or default position, such as that there is no relationship between two quantities, or that there is no difference between a treatment and the control.
The term was originally coined by English geneticist and statistician Ronald Fisher. In some versions of hypothesis testing using statisti(such as developed by Jerzy Neyman and Egon Pearson), the null hypothesis is tested against an alternative hypothesis.

***This alternative may or may not be the logical negation of the null hypothesis. The use of alternative hypotheses was not part of Ronald Fisher's formulation of statistical hypothesis testing, though alternative hypotheses are standard today in practc.
For instance, one might want to test the claim that a certain drug reduces the chance of having a heart attack. One would choose the null hypothesis "this drug does not reduce the chances of having a heart attack" (or perhaps "this drug has no effect on the chances of having a heart attack").
One should then collect data by observing people both taking the drug and not taking the drug in some sort of controlled experiment. If the data are very unlikely under the null hypothesis one would reject the null hypothesis, and conclude that its negation is true.
That is, one would conclude that the drug does reduce the chances of having a heart attack. Here "unlikely data" would mean data where the percentage of people taking the drug who had heart attack was significantly (according to statistical standards) less than the percentage of people not taking the drug who had heart attacks.
Of course one should use a known statistical test to decide how unlikely the data were and hence whether or not to reject the null hypothesis.


***One must take care in choosing a null hypothesis, as different choices lead to different answers. This is demonstrated in the following example: You are asked to decide if the coin is fair (i.e. that on average it will come up heads 50% of the time). You flip it 5 times and it comes up heads all 5 times. Do you conclude it is not a fair coin? Well, you might say your alternate hypothesis is "this coin is biased towards heads". The null hypothesis would be "this coin is not biased towards heads", which is to say it is at least as likely to come up tails as heads. Under this null hypothesis, the data are indeed unlikely (it should happen about 3% of the time). You would reject the null hypothesis and conclude the coin was biased. However, you could instead choose the alternate hypothesis "this coin is biased", and the null hypothesis, "this coin is fair". Then the data are not so unlikely; similar data should happen about 6% of the time, where 3% of the time you get all heads and 3% of the time you get all tails. You would then not reject the null hypothesis, so you would make no conclusion. In this case, the second null hypothesis would be correct: you were originally asked to decide if the coin is fair, not if it is biased towards heads. You would want more data to make any such conclusion (and really you should have wanted more data to begin with). This second example illustrates one hazards of hypothesis testing: if one tests a given set of data with respect to a large number of null hypotheses, all of which are true, one is nonetheless likely to reject some of them, making false conclusions. However, if one follows the scientific method and formulates the null hypothesis before collecting data, one only makes a small number of type 1 errors (i.e. one only rejects a true null hypothesis a small percentage of the time). Of course, even if used carefully and correctly, any statistical test gives some incorrect conclusions***.



Remember you can only refine towards truth with something that DIS proves something by a PROOF is that is found that makes the hypothesis impossible.

The absence of something can never be used for causality.
The best that it can do is lead more credibility to that which can only replace what makes the original premise impossible to perform. WE SEARCH FOR VALIDITY NOT THE INVALID.

For all of the behaviorist our there:

Punishment is a fallacy of the mind. It is always a force of negative reinforcement.

YOU CANNOT CREATE THE ABSENCE OF A BEHAVIOR.

Logic states that you cannot prove the existence of something with the absence of evidence.

An anomaly in the Norway Spiral doesn't necessarily mean its a rocket.
A quick man would say that its a rocket.
A smart man would say that it is probably a rocket, but I don't have enough evidence yet.
A wise man would say that Americans pay attention to POPmedia too much.
And the illuminated man would not give two cents about the spiral.

Anti-gravity has been hoaxed by several people, but that does not mean that it is not real.
It only means that certain hoaxers are not real.

Lost are ye who may never find truth.

[edit on 3/30/2010 by Josephus23]




posted on Mar, 30 2010 @ 12:19 AM
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S+F!!!!!!!!

Very nice thread! One must not be a crude skeptic but one that reasons through the proper logic instead of a biased one.

The goal is to not prove outlandish theories wrong... the goal is to find out the facts and then make a decision: true or false.

More can be done searching for the truth than searching for fallacy.



posted on Mar, 30 2010 @ 12:38 AM
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I myself have been guilty of this...

Thanks for the nudge!




posted on Mar, 30 2010 @ 01:11 AM
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reply to post by Signals
 


Man I am glad to see that my goal was to inform and not get my butt chewed.

I hope that more people see this and respond.

A part of me doubts it, highly, but it is hard to break away from being an adrenaline junky, and the sugar high media blitz we get everyday gives us more than enough .

Just keep doing these 4 things:
1)make no assumptions.
2)never take anything personally
3)always do your best
4)be impeccable with your word.

Thanks for the contribution.

peese.



posted on Mar, 30 2010 @ 06:17 PM
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well, it's a circle. a lack of evidence for something doesn't mean that something doesn't exist. but a lack of evidence for DISproving something doesn't mean that something exists either. like you say, it is unknown.

the idea that skeptics engage in this phenomenon, at the exclusion of non-skeptics is weird to me. i see the opposite more often than not: someone will declare X assertion. people will celebrate the assertion with glee. a skeptic will say "prove X." the non-skeptic will say i don't have to prove X, you prove X isn't. people will again celebrate because if it can't be proven that X isn't, then X must be!

skeptics don't deny X, they ask for proof in order to formulate an opinion. that's why their "skeptical."

without proof (evidence), an opinion on X can be difficult for some to develop, but freeing for others. but skeptics don't deny X.

we all acknowledge there are things we currently lack the ability to know. but should we believe, or even consider, every possible scenario, involving things we don't know, as if it has the merit of things we do know? i'm sure many people feel like we should. others, and often skeptics, do not feel this way.

i'm not sure whether i'm agreeing with you or not, Joe, it kinda gets foggy if you think about it for a while.

[edit on 3/30/2010 by Hadrian]



posted on Mar, 30 2010 @ 07:31 PM
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reply to post by Hadrian
 


I couldn't agree with you more.

The reason that this is so foggy is because people on both sides of any argument fall prey to this mistake.

I am not trying to bash skeptics, at all.
I continually see people on ATS using a lack of evidence to substantiate a conclusion on the believers side as well.

But what I see happening much more frequently are pseudoskeptics who point to a lack of evidence as an invalidation.
And that is not how science works.

My entire point is that it is NOT in ANY way possible to prove that anything does not exist.
It is not possible to prove a negative.

The best that anyone can do is prove that something exists that makes it impossible for the hypothesis in question to exist.

It is not possible to prove a nothing, and that is the MO of nearly 90% of the so-called skeptics found on ATS.

And you are totally correct in another aspect of your comment as well.
This can go either way between skeptics and believers and most of the time in "real" life the fault rests with the "believers", but I see so many skeptics on boards saying stuff like..

(fill in the blank) doesn't exist or it is not possible because the evidence shown is a hoax, or it is not valid evidence.

And that is simply not how the scientific method works.

That is not a scientifically sound statement.

We can only say that things exist. Period.
The only way to invalidate something is to PROVE something exists that makes it impossible for the questionable hypothesis to exist.

Dig?



posted on Mar, 30 2010 @ 10:07 PM
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reply to post by Josephus23
 


i dig. whew, i was kinda worried i might be in for a real learning.



posted on Mar, 30 2010 @ 11:52 PM
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reply to post by Hadrian
 


You still could be learning something.

Just look around for what I am talking about and you will see it EVERYWHERE.

The biggest reason for this is
correlation does not imply causation.

Just know that something can never be disproved. The best that can happen is that something else is proven that makes it impossible for the hypothesis at hand to exist.

Thank you for the reply however.

You response made me think much more deeply about my OP and I am always extremely appreciative when someone can engage in a rational discussion without the name calling and such.

In fact, I gave you a star because you pointed out the parts in my OP that were vague, nebulous, and confusing.

Thank you for that.

Cheers mate.



posted on Mar, 31 2010 @ 01:13 AM
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DOUBLE POST SORRY!!

[edit on 3/31/2010 by Josephus23]



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