Calculating Probabilities with Visual Basic: A Practical Guide

In summary: The logic in that equation is that x! is the exact (exact!) sum of x^x, where x is any number between 0 and 1 million.
  • #1
JPC
206
1
Hey, let's take for example the probabilities when u throw 100 times a coin (lets say it can't be corner)

ok , the probability is obviously 50 : 50

but , what's the probability that your results are same as the probability for this case
 
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  • #2
The probability of what is '50 : 50' ? :wink:
 
  • #3
well

well if u throw 100 times a coin
the probability is : 50 heads, 50 tails
 
  • #4
In other words, you want the probability of throwing exactly 50 heads (and 50 tails) in 100 tosses, any order of heads and tails.

Is this homework? If so, please show what you have done. If not, I (or someone else here) will show you how to compute such a probability.
 
  • #5
JPC said:
well

well if u throw 100 times a coin
the probability is : 50 heads, 50 tails

Not for any coin. Only for an unbiased coin P(Head)=P(Tail) in a single toss = 0.5, assuming that there is no other outcome of the toss.
Getting 50 heads and 50 tails is an event, it is not a probability.
Again, if P(H)=0.5 then "50 heads" is the "expected" number of heads in 100 throws...it is not a probability.
Now comming to your question: If you denote the no. of heads in 100 tosses by X, then X~Bin(100,0.5). Find P(X=50).
 
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  • #6
ssd said:
If you denote the no. of heads in 100 tosses by X, then X~Bin(100,0.5). Find P(X=50).

What does that mean , i don'k know all the conventions yet ?

and its not for homework
 
  • #7
ssd was talking about random variables. You may want to google-up that term.
 
  • #8
In particular, ssd was talking about a random variable with a binomial probability distribution, which applies only if the coin is unbiased and tosses are independent. Assuming an unbiased coin and indepdendent tosses, the answer to the original question is
[tex]\frac{100!}{50!\,50!}\;\frac 1 {2^{100}} \approx 0.0796[/tex]
 
  • #9
D H said:
In particular, ssd was talking about a random variable with a binomial probability distribution, which applies only if the coin is unbiased and tosses are independent. Assuming an unbiased coin and indepdendent tosses, the answer to the original question is
[tex]\frac{100!}{50!\,50!}\;\frac 1 {2^{100}} \approx 0.0796[/tex]

Right you are. I did not mention the fact that the sum of Bernoullian trials will be Binomial if those trials are independent. Actually I really was focused on the statement of the problem.
 
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  • #10
hey , u didnt put any operator between the 50! and 50!
is it multiply ?

and , u didnt put any operator between the two fractions, is it also multiply ?

because , if it is , doesn't look very much like 0.0796

100! : 5050
50! : 1275
50!² : 1625625

5050 / (1625625 * 2^100) = 2.45...and, also, in general terms, what is the logic between this equation ?
 
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  • #11
I'm not that good at probability, but the vinculum affects the order of operations, i.e.
[tex]\frac{100!}{50!50!} \frac{1}{2^{100}} = ( 100! / 50!50! ) * ( 1 / 2^{100} ) = 0.0795892374[/tex]
 
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  • #12
JPC said:
because , if it is , doesn't look very much like 0.0796

100! : 5050
50! : 1275
50!² : 1625625

5050 / (1625625 * 2^100) = 2.45...

Wha...? 50! is a huge number with 65 digits, it's a lot bigger than 1275. 1275 = 50 + 49 + ... + 2 + 1, while 50! = 50 * 49 * ... * 2 * 1.
 
  • #13
oh damn , i made a mistake
the ! is a multiplication , not addition, not 0.5(n² + n)

i see my mistake
 
  • #14
but , how do u translate x! then ?

like what's the equation to find it
like if u want to find the sum of all the numbers from 0 to x its : 0.5(x + x²)
but what is it for the multiplication ?
 
  • #15
JPC said:
but , how do u translate x! then ?

like what's the equation to find it
like if u want to find the sum of all the numbers from 0 to x its : 0.5(x + x²)
but what is it for the multiplication ?

There's no polynomial that gives a value close (for any reasonable definition of "close") to x! for all positive x.

There are some approximation formulas; (x/e)^x ~ x! would be one of the simplest*, where e = 2.71828...

If you want the exact answer you're just going to have to multiply it out, though. For this problem that's pretty much all you can do. Notice, though, that 100!/50! = 100 * 99 * ... * 51 * 50 * 49 * ... * 2 * 1 / (50 * 49 * ... * 2 * 1) = 100 * 99 * ... * 52 * 51.

* I hope I got this right, it's from memory. There are much better ones if you need more accuracy; Gosper's reformulation of Stirling's estimate is pretty good.
 
  • #16
better solution (if x is smaller than 1 million)
learn visual Basics , and make a program to do it for you using 'do until' - 'loop'


But what's the logic in that equation ?
how can i make an equation like that for other cases ?
whats the clear syntax ?
 
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1. What does "Probability of a Probability" mean?

Probability of a Probability refers to the likelihood or chance that a certain probability will occur. In other words, it is the probability of an event happening based on the probability of another event occurring.

2. How is "Probability of a Probability" calculated?

The calculation of Probability of a Probability involves multiplying the probabilities of the two events together. This is known as the "product rule" in probability theory.

3. Can the "Probability of a Probability" ever be greater than 1?

No, the Probability of a Probability cannot be greater than 1. This is because the maximum probability of an event occurring is 1, so multiplying it by another probability will never result in a value greater than 1.

4. How is "Probability of a Probability" used in real life?

The concept of Probability of a Probability is commonly used in risk assessment and decision-making. It can also be used in fields such as economics, finance, and insurance to calculate the likelihood of certain events occurring.

5. What is the difference between "Probability of a Probability" and "Conditional Probability"?

While both concepts involve calculating the likelihood of an event based on another event, Conditional Probability specifically refers to the probability of an event occurring given that another event has already occurred. Probability of a Probability, on the other hand, looks at the probability of two events occurring together.

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