2. SUPPLEMENTAL QUESTION 1 (a) Toss a fair coin so that with probability pheads occurs and...
Suppose we toss a fair coin every second so the first toss is at time t1. Define a random variable Y (the "waiting time for the first head ") by Prove that Yi satisfies (Yİ is said to have geometric distribution with parameter p. (Yi-n) = (the first head occurs on the n-th toss). FOUR STEPS TO THE SOLUTION (1) Express the event Yǐ > n in terms of , where , is the number of heads after n tosses...
A fair coin is tossed n times. Let X be the number of heads in this n toss. Given X = x, we generate a Poisson random variable Y with mean x. Find Var[Y]. Answer depends on n.
On a single toss of a fair coin, the probability of heads is 0.5 and the probability of tails is 0.5. If you toss a coin twice and get heads on the first toss, are you guaranteed to get tails on the second toss? Explain.Explain why – 0.41 cannot be the probability of some event.Explain why 1.21 cannot be the probability of some event.Explain why 120% cannot be the probability of some event.Can the number 0.56 be the probability of...
Suppose we toss a coin (with P(H) p and P(T) 1-p-q) infinitely many times. Let Yi be the waiting time for the first head so (i-n)- (the first head occurs on the n-th toss) and Xn be the number of heads after n-tosses so (X·= k)-(there are k heads after n tosses of the coin). (a) Compute the P(Y> n) (b) Prove using the formula P(AnB) P(B) (c) What is the physical meaning of the formula you just proved? Suppose...
Q3. Suppose we toss a coin until we see a heads, and let X be the number of tosses. Recall that this is what we called the geometric distribution. Assume that it is a fair coin (equal probability of heads and tails). What is the p.m.f. of X? (I.e., for an integer i, what is P(X=i)? What is ?[X]? ({} this is a discrete variable that takes infinitely many values.)
4. Toss a fair coin 6 times and let X denote the number of heads that appear. Compute P(X ≤ 4). If the coin has probability p of landing heads, compute P(X ≤ 3) 4. Toss a fair coin 6 times and let X denote the number of heads that appear. Compute P(X 4). If the coin has probability p of landing heads, compute P(X < 3).
Question 2 Suppose you have a fair coin (a coin is considered fair if there is an equal probability of being heads or tails after a flip). In other words, each coin flip i follows an independent Bernoulli distribution X Ber(1/2). Define the random variable X, as: i if coin flip i results in heads 10 if coin flip i results in tails a. Suppose you flip the coin n = 10 times. Define the number of heads you observe...
A fair coin is tossed 3 times. Let X denote a 0 if the first toss is a head or 1 if the first toss is a zero. Y denotes the number of heads. Find the distribution of X. Of Y. And find the joint distribution of X and Y.
Toss a fair coin 4 times. Let Y be the number of heads. (a) What is the probability mass function of Y ? Compare your answer to the probability mass function of Binomial distribution. (b) What is the cumulative distribution function of Y ? (c) What is the expected value of Y ? (d) What is the variance of Y?
a. Suppose that a fair coin is tossed 15 times. If 10 heads are observed, determine an expression / equation for the probability that 7 heads occurred in the first 9 tosses. b. Now, generalize your result from part a. Now suppose that a fair coin is to be tossed n times. If x heads are observed in the n tosses, derive an expression for the probability that there were y heads observed in the first m tosses. Note the...