What is the Probability Function for Tossing a Coin 10 Times?

In summary, the probability of obtaining a certain number of heads when tossing a fiat coin 10 times independently can be calculated using the binomial distribution formula, which takes into account the number of trials, probability of success, and probability of failure. This distribution is inherently discontinuous at non-integer values since only integer number of successes are possible in a given number of trials.
  • #1
1MileCrash
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Suppose that a fiat coin is tossed 10 times independently. Determine the pf of the number of heads that will be obtained.

I'm feeling really out of touch with this material. It seems like any number of heads is equally likely but I know that just can't be right.

My reasoning for saying such is that the probability of a head is 1/2 and the probability of a tail is 1/2,

So the probability of a head, then tail, then head is

(1/2)(1/2)(1/2)

Or head, head, head is

(1/2)(1/2)(1/2)

But I know that getting 5 heads in the ten flips and getting all heads aren't equally likely.. are they?

So can someone "remind" me how my thinking is wrong?
 
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  • #2
Wait, I think I see. The probability of any order of heads or tails is equally likely, but the number of "ways" 5 heads can occur is more than the number of ways 10 can occur (which is just one.)

So

f(x) = (10 CHOOSE x)(1/2)^10

Right?
 
  • #3
Yes. You might want to review the binomial distribution.
 
  • #4
Indeed. Should I also make the function piecewise, 0 for any exception to the integer interval 1 through 10?
 
  • #5
Since each trail can be classified as a simple success or failure, we use the binomial distribution, as you have already written down for this case. Just incase, the general form is:

[itex] P(X) = C^{n}_{x}p^{x}q^{n-x} [/itex]

where:
p = probability of success in a trial
q = probability of failure = (1-p)

Edit: Yes, the distribution is inherently discontinuous at non-integer values since there can only be an integer number of successes in n trails.
 

FAQ: What is the Probability Function for Tossing a Coin 10 Times?

What is a probability function?

A probability function is a mathematical function that maps the likelihood of an event occurring to a numeric value between 0 and 1. It is used to model random processes and is an important tool in statistics and probability theory.

How do you write a probability function?

To write a probability function, you first need to identify the random variable and the possible outcomes of the event. Then, assign a probability to each outcome and use a mathematical formula to combine these probabilities. The resulting function will represent the probability of each outcome.

What is the difference between a probability function and a probability distribution?

A probability function is a mathematical representation of the probabilities of all possible outcomes of an event, while a probability distribution is a table, graph, or formula that shows the probabilities of each possible outcome. In other words, a probability function is a theoretical concept, while a probability distribution is a visual or numerical representation of that concept.

How do you determine the validity of a probability function?

A probability function is considered valid if it satisfies two conditions: the probabilities assigned to each outcome must be between 0 and 1, and the sum of all probabilities must equal 1. Additionally, the function should accurately reflect the nature of the event it is modeling.

Can a probability function be used for continuous random variables?

Yes, a probability function can be used for both discrete and continuous random variables. For continuous variables, the function is often represented by a probability density function, which describes the probabilities as a function of the variable's values rather than individual outcomes.

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