Having won a bet is a matter of luck, not your feat, although fairly estimating an effective probabilities distribution can be a feat.
Topics
About: bias
About: probability
The table of contents of this article
- Starting Context
- Target Context
- Orientation
- Main Body
- 1: Having Won a Bet Is Not Your Feat
- 2: The Mentality Entails Grave Harm, in Fact
- 3: Let Us Understand the Concept of Probability, Correctly
- 4: Of Course, There Are Effective Populations and Ineffective Populations, Though
- 5: Sampling Has to Be Done Fairly
- 6: Beware of Statistical Frauds, but . . .
Starting Context
- The reader knows the background of this site.
Target Context
- The reader will understand that claiming credit for having won a bet is ludicrous and very harmful.
Orientation
What we are supposed to do is to maintain the unboundedly consistent hypotheses system.
To establish the unbounded consistency is the only way to near truths.
Main Body
Stage DirectionHere is Special-Student-7 in a room in an old rather isolated house surrounded by some mountains in Japan.
1: Having Won a Bet Is Not Your Feat
Special-Student-7-Hypothesizer
A very ludicrous act is to claim credit for having won a bet.
Special-Student-7-Rebutter
Do you mean that someone says that having won the bet is his or her feat?
Special-Student-7-Hypothesizer
He or she says so directly or indirectly.
Special-Student-7-Rebutter
When you say "indirectly" . . .
Special-Student-7-Hypothesizer
He or she boasts of his or her having won the bet.
Special-Student-7-Rebutter
Certainly, if he or she did not think that it was his or her feat, there would be no reason to boast of it.
Special-Student-7-Hypothesizer
We are talking not only about dice bets, roulette, etc. but also about trading stocks, predicting the winner of a baseball league season, assuming that someone is a thief, in fact, assuming anything not on absolutely solid grounds.
Special-Student-7-Rebutter
Although betting one's own money on dice is just a personal matter, assuming that someone is a thief is a serious matter.
Special-Student-7-Hypothesizer
Does someone not understand that winning any bet is a matter of luck?
Special-Student-7-Rebutter
The problem is that someone boasts of having won a single bet.
Special-Student-7-Hypothesizer
If the results of a significant number of tries fairly approximate your probabilities distribution estimation, you may be able to legitimately boast of having made the estimation, but boasting of a single win is ludicrous.
2: The Mentality Entails Grave Harm, in Fact
Special-Student-7-Rebutter
The mentality of claiming credit for having won a bet is of course laughable, but it is not something to be let pass as simply amusing.
Special-Student-7-Hypothesizer
The mentality means that the person is assuming that he or she possesses some supernatural power that can tell things not on absolutely solid grounds, which is really a grave problem.
In fact, he or she begins to declare that someone is a thief, a terrorist, or a lawyer, not on absolutely solid grounds.
Assuming to possess some supernatural power may seem an innocent ignorance, but falsely declaring someone to be a thief, or a lawyer, is hardly "innocent".
Special-Student-7-Rebutter
Being ignorant more or less is of course unavoidable for tiny-brained humans, but not admitting one's ignorance is really a sin.
3: Let Us Understand the Concept of Probability, Correctly
Special-Student-7-Rebutter
We all have to understand the concept of probability correctly, because while almost all the matters in human life have to be judged probabilistically, if some people do not understand the concept of probability correctly, what kinds of injustices are being performed daily?
Special-Student-7-Hypothesizer
Serious kinds, I guess.
The most important thing to be always aware of about probability is that any probability depends on the choice of population.
For example, in the case of weather forecasting, the rain probability for any day is about choosing a significantly large population of some past days that resemble the concerned day and counting the days in which some rain had fallen.
Special-Student-7-Rebutter
"resemble" depends on the criteria by which some days are deemed to resemble the concerned day.
Special-Student-7-Hypothesizer
The choice of the criteria is essentially arbitrary; for example, all the days can be deemed to resemble the concerned day, in virtue of having 24 hours, which is a kind of criteria.
Then, the rain probability for the day will be just the yearly rain probability; I mean, if it rains 73 days in 365 days, the probability will be 20%.
Special-Student-7-Rebutter
If a weather forecaster does so for every day, the rain probabilities for all the days will be the same 20%, insipid, but not wrong in any way.
Special-Student-7-Hypothesizer
Usually, different populations are used for different days, which is the reason why the weather forecast for a day is different from the one for another day.
Special-Student-7-Rebutter
The population for each day is chosen by some criteria that are usually about distributions of cloud, temperature, pressure, etc.
Special-Student-7-Hypothesizer
It is important to understand that probability is about human ignorance, at least usually.
For example, it is in fact determined whether it will rain tomorrow or not, although humans cannot know it in their technology, because the phenomenon is too complex for them to be able to grasp the full initial condition and compute the future based on the full initial condition.
Special-Student-7-Rebutter
There will be some people who claim that indeterministicness of quantum mechanics is not about human ignorance.
Special-Student-7-Hypothesizer
In fact, I do not buy that claim, but anyway, I put "at least usually" in view of the claim.
At least, uncertainties of weather forecasts, earthquake predictions, etc. are not the consequences of quantum phenomena, at least mainly.
Whether an earthquake happens when is determined, although humans do not have the ability to know it.
4: Of Course, There Are Effective Populations and Ineffective Populations, Though
Special-Student-7-Hypothesizer
I said "The choice of the criteria is essentially arbitrary", but of course, there are effective populations and ineffective populations.
Special-Student-7-Rebutter
What populations are effective?
Special-Student-7-Hypothesizer
Decisive populations, I say: if it is nearly 100% rain or nearly 0% rain for the population, the population is decisive.
Special-Student-7-Rebutter
The population has to have a significant size as a precondition.
Special-Student-7-Hypothesizer
Of course.
But I wonder whether I am allowed to choose any skewed population if the population is decisive.
Special-Student-7-Rebutter
That depends on your purpose, I think.
Special-Student-7-Hypothesizer
What do you mean?
Special-Student-7-Rebutter
If your purpose is solely to predict the outcome, however skewed population will be fine, if it is really decisive.
Special-Student-7-Hypothesizer
What else could my purpose be?
Special-Student-7-Rebutter
Your purpose could be to claim a statistical distribution.
For example, you may claim that the crime rate for a race is high.
Special-Student-7-Hypothesizer
But the crime rate for every race may be high . . .
Special-Student-7-Rebutter
It will be naturally guessed that the population has been chosen so with a necessity, so, it will be naturally guessed that the crime rate is high only for the race.
Your claim is not particularly wrong, but it is maliciously misleading.
Special-Student-7-Hypothesizer
So, we should not unnecessarily narrow the population.
5: Sampling Has to Be Done Fairly
Special-Student-7-Rebutter
Let us not confuse sample with population: taking a smaller sample of the population is OK, because it is often difficult to survey the whole population, and taking a smaller sample is not narrowing the population.
Special-Student-7-Hypothesizer
But the sampling should not be skewed anyway, of course.
Special-Student-7-Rebutter
Skewing of sampling is more malicious, because it can be done utterly surreptitiously: some undesired samples can be just ditched secretly.
Special-Student-7-Hypothesizer
Someone can ditch some undesired samples in order to draw his or her pre-desired conclusion.
And it can be easily done as he or she can just forget having picked up the sample; as in prevalent answers by politicians, he or she just does not have the memory!
Special-Student-7-Rebutter
We have to learn that human impressions should not be trusted, because people filter things egoistically or neurotically.
6: Beware of Statistical Frauds, but . . .
Special-Student-7-Hypothesizer
You should not be deceived by numbers as though any number should be accurate by sole virtue of being a number.
A statistical number may be of an unnecessarily narrowed population or by a skewed sampling.
Special-Student-7-Rebutter
Or the sampling may not have been large enough; you should not be taken in by any conclusion drawn based on any insignificant sampling.
Special-Student-7-Hypothesizer
On the other hand, there is an issue of whether one should spurn any statistical numbers he or she does not like, claiming that they are frauds.
Special-Student-7-Rebutter
1st, they can be frauds, but he or she cannot declare that they are frauds, not on absolutely solid grounds; 2nd, to not accept any number unless one personally confirms its accuracy is a legitimate attitude, I think, but rejecting undesired numbers while accepting desired numbers without confirming their accuracies is not legitimate at all.
