1. Suppose that random variables X and Y are independent and have the following properties: E(X) = 5, Var(X) = 2, E(Y ) = −2, E(Y 2) = 7. Compute the following. (a) E(X + Y ). (b) Var(2X − 3Y ) (c) E(X2 + 5) (d) The standard deviation of Y
. 2. Consider the following data set: �x = {90, 88, 93, 87, 85, 95, 92} (a) Compute x¯. (b) Compute the standard deviation of this set.
3. Suppose that there is a classroom with 20 students. Each of those students independently flips a fair coin. (a) What is the probability that exactly 13 students will flip HEADs and 7 students will flip TAILs? (Do not use a table) (b) Use the binomial table for this question. What is the probability that at least 13 students will flip HEADs? (c) Is the outcome of 13 HEADs more than one standard deviation above expected outcome?
4. Suppose that there is a classroom of 200 students. Among those students, 50 are from the West, 75 are from the East, 25 are from the North, and 50 are from the South. Suppose I decide to form a committee of 8 students. (a) What is the probability that there will be exactly 3 students from the South? (b) What is the expected number of students from the South? (c) What is the standard deviation for the number of students from the South?
5. Suppose that in a city of 10,000 people, there are 4,000 who like football and 6,000 who do not. Suppose that we conduct a poll of 16 citizens. What is the probability that at least half of those polled like football? (Use Binomial approximation to find a decimal answer.) 1
6. Suppose that a random variable X is an Exponential Random Variable with parameter β = 3. (a) What is E(X)? (b) Compute P(X > 2). (c) Compute P(X > 5 | X > 3).
7. An assembly line at a plant produces exactly 10000 widgets a day. Suppose that approximately 1 out of every 2000 fails a standards test and is thrown out. What is the probability that there will be 10 or more widgets thrown out on a given day?
8. There are 100 green balloons and 150 red balloons in a bag. Suppose we extract 10 balloons from the bag. (a) What is the exact probability that five of the balloons will be green? (b) Use Binomial Approximation to find the probability that exactly five of the balloons will be green. (c) Use Binomial Approximation to find the probability that no more than four of the balloons are green.
9. Suppose that X is a continuous random variable and is uniformly distributed over the interval [10, 20]. (a) What is P(X > 13)? (b) What is P(X > 13 | X < 17)?
10. The heights of women in the US are roughly normally distributed with a mean of 54 inches and a standard deviation of 3 inches. (a) Suppose there will be a new student attending class next week. What is the probability that she will be taller than 60 inches? (b) Let X represent the height of a new student. For what value k is it true that P(X > k) = 0.01?
11. Historically, the grade distribution for a certain test has been normally distributed with a mean of 80 and a standard deviation of 5. Sally is taking the exam next week and wants to know the probability that she will score at least a 90. If she assumes her outcome will be like those of students who have taken the class in the past, what is this probability?
12. Suppose that Z is a standard normal random variable. (a) Compute P(Z > 1.5). (b) What is the probability that Z is larger than 1.5 given that it is positive?
13. Suppose that the number of bees in a flower patch is roughly 5 per square meter. A gardener has a flower patch that is 3 m by 1 m. (a) What is the probability that there will be between 10 and 20 bees in the patch (inclusive of 10 and 20)? (b) What is the largest value k such that P(X ≤ k) = 0.05?
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1. Suppose that random variables X and Y are independent and have the following properties: E(X)...
Suppose you flip a coin 15 times and let x be the discrete random variable of the number of heads obtained. Use the binomial distribution table to find each of the following probabilities. (A) p(exactly 8 heads)= (b) p(at least one head)= (c) P(at most 3 heads)=
. Discrete Distributions. Suppose I flip a coin 40 times. The flips are independent. The probability the coin will come up heads is 40% at each flip. Let X be the number of heads observed in the 40 flips. 26. What is the expected value of X? 27. What is the variance of X? 28. What is P(X 18)? 29. What is P(X 2 18) 30. Using the normal approximation to the binomial with the conti 31. Is the normal...
A. Let X be a binomial random variable with n = 74 and p = .6. Use the normal approximation to the binomial to find: (i) P(X ≤ 50) (iii) P(40 ≤ X ≤ 50) (v) P(X = 43) (ii) P(X ≥ 40) (iv) P(42 ≤ X < 49) B. Each time a roulette wheel is spun, there are 38 possible outcomes, 18 red, 18 black, and two green. Suppose that you ALWAYS bet "black". (i) Suppose the roulette wheel...
Binomial Random Variables A survey of 933 Intro Stat students produced the following results. Frequency table Count = 933 Tattoos Frequency No 700 Yes 233 What is the probability that an Intro Stat student has a tattoo? 0.20 Suppose we take a random sample of 15 students taking Introductory Statistics this semester and observe the number who have tattoos. Let X = # of students with tattoos observed out of the 15 students What are the possible values of X?...
(Using Central Limit Theorem) Let S100 sum of 100 independent Bernoulli (toss a coin) random variables. 1. Find P(S 100 > 55) exactly using Minitab CDF command (Binomial n=100, p=0.5). 2. Approximate this probability using bell curve approximation--Normal mean = 0 and standard deviation 1.
Suppose X and Y are independent Binomial random variables, each with n=3 and p=9/10. a. Find the probability that X and Y are equal, i.e., find P(X=Y). b. Find the probability that X is strictly larger than Y, i.e., find P(X>Y). c. Find the probability that Y is strictly larger than X, i.e., find P(Y>X).
3. Suppose there are 2 urns such that the first urn contains a white balls and b black balls and the second urn contains c white balls and d black balls. Flip a coin whose probability of landing heads is p and select a ball from the first urn if the outcome is heads and from the second if the outcome is tails. What is a value for p for which the probability that the outcome was heads given that...
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...
3Y 2 1. (20 points) Suppose that X and Y independent random variables. Let W 2x (a) Consider the following probability distribution of a discrete random variable X: 12 P(X) 00.7 0.3 X Compute the mean and variance of X (b) Use your answers in part (a). If E(Y)=-3 and V(Y)= 1, what are E(W) and V (W)?
2) Suppose the weight of a newborn baby follows a normal distribution with a mean of 3500 grams and a standard deviation of 600 grams. a. What is the probability that the weight of a randomly selected newborn exceeds 4000g? b. For a random sample of 36 newborns, what is the probability that their mean weight is less than 3450g? 3) Suppose that 5% of American adults are vegetarian. Find the probability that in a random sample of 500 American...