Tossing a Fair Coin: Probability Mass Function

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In summary, the probability of getting a head on the first toss of a fair coin is 1/2. The probability of getting a head on the second toss of a fair coin is 1-P(X≤n) = 1-\sum \limits_{k=1}^n(1/2)x+1. If the first toss is repeated n times, the probability of getting a head on the nth toss is 1/2+n*(1-P(X≤n)).
  • #1
VantagePoint72
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Homework Statement



A fair coin is tossed repeatedly and X is the number of tosses before the first head appears. You independently repeat the experiment, and Y is the number of tosses before the first head appears in the second sequence of tosses.
a. Give the probability mass function of X
b. Find P(X>n), for n≥1
c. Find P(X=Y)
d. Find P(X>Y)

Homework Equations



Geometric pmf: p(x) = p(1-p)x-1

The Attempt at a Solution



a. I believe this should be P(X=x) = (1/2)x+1. Is this correct so far?

b. P(X>n) = 1 - P(X≤n) = 1 - [itex]\sum \limits_{k=1}^n[/itex](1/2)x+1

I feel like a closed form for this is expected. I know there's some kind of formula for sums of powers, but we never looked at it in class. So, I'm wondering if there's another way to do this question.

c. P(X=Y) = [itex]\sum \limits_{k=1}^∞[/itex](1/2)2x+2

Is this correct? If so, same issue with explicitly evaluating the sum as with b.

d. Since the problem is symmetric with respect to X and Y, presumably the answer is:
P(X>Y) = 0.5*[1-P(X=Y)]
Thus, I need the closed form solution from c. This solution relies on the fact that X and Y have the same distribution. Is there a more general method for this?
 
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  • #3
Baha oh my head is stupid tonight, it seems. Aside from that, are my answers correct?
 
  • #4
LastOneStanding said:
Baha oh my head is stupid tonight, it seems. Aside from that, are my answers correct?

Yes, except for your not defining what, exactly, you mean by x and what is its range. You see, x is different in the geometric distribution p(x) = p(1-p)x-1 and in your P(X=x) = (1/2)x+1. Defining what your symbols mean is an important part of the solution process.

RGV
 
  • #5
Good point, I've let myself get a little sloppy. Thanks Dick and Ray!
 

1. What is the probability of getting heads or tails when tossing a fair coin?

The probability of getting heads or tails when tossing a fair coin is 0.5 or 50%. This is because there are only two possible outcomes and each has an equal chance of occurring.

2. How does the probability mass function (PMF) relate to tossing a fair coin?

The probability mass function (PMF) is a mathematical function that assigns probabilities to each possible outcome of a random variable. In the case of tossing a fair coin, the PMF would assign a probability of 0.5 to both the outcome of heads and tails.

3. Can the PMF be used to predict the outcome of a single coin toss?

No, the PMF cannot be used to predict the outcome of a single coin toss. It is a theoretical concept that describes the probabilities of all possible outcomes, but it does not guarantee a specific outcome for a single event.

4. How does the PMF change if the coin is not fair?

If the coin is not fair, meaning it is biased towards one side, the PMF would assign a higher probability to the outcome of the biased side and a lower probability to the other side. In this case, the PMF would no longer be symmetrical like it is for a fair coin.

5. Can the PMF be used to calculate the expected number of heads or tails in multiple coin tosses?

Yes, the PMF can be used to calculate the expected number of heads or tails in multiple coin tosses. This is because the PMF provides the probabilities for each outcome, and the expected number of heads or tails can be calculated by multiplying the number of tosses by the probability of the specific outcome.

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