4 Probability Objectives: Understand the need for and application of
... the set of all possible outcomes in the problem context S = {x,y,z,…} and n(S) = number of all possible outcomes Introduce terminology related to Event (outcomes that we are interested in) and probability of an event: event A = {y, z, …}; n(A) = number of outcomes in A, P(A) = n(A)/n(S) Review 3 way ...
... the set of all possible outcomes in the problem context S = {x,y,z,…} and n(S) = number of all possible outcomes Introduce terminology related to Event (outcomes that we are interested in) and probability of an event: event A = {y, z, …}; n(A) = number of outcomes in A, P(A) = n(A)/n(S) Review 3 way ...
Dependent Events
... white sweatshirt. He also has blue, red, and gray sweatpants. If Zachary randomly pulls a sweatshirt and a pair of sweatpants from his drawer, what is the probability that they will both be blue? A. B. C. D. ...
... white sweatshirt. He also has blue, red, and gray sweatpants. If Zachary randomly pulls a sweatshirt and a pair of sweatpants from his drawer, what is the probability that they will both be blue? A. B. C. D. ...
SOLUTIONS ACTIVITY 5
... a randomly selected student would be greater than 4. Show work. P (rating > 4) = 1 – P(rating ≤ 4) = 1- .42 = .58 3 Suppose somebody randomly guesses at every one of 20 True-False questions. a. The number of correct guesses is a binomial random variable. What are the values of the parameters n and p ...
... a randomly selected student would be greater than 4. Show work. P (rating > 4) = 1 – P(rating ≤ 4) = 1- .42 = .58 3 Suppose somebody randomly guesses at every one of 20 True-False questions. a. The number of correct guesses is a binomial random variable. What are the values of the parameters n and p ...
What is the range of possible outcomes? The Range of Probability
... Now let’s look at the other extreme. We want to win so badly that we were first in line to buy tickets. We bought all 100 tickets. Now we know that one of our numbers will have to be picked from the box. We are certain of it. Our chances of winning are 1.00 or 100%: ...
... Now let’s look at the other extreme. We want to win so badly that we were first in line to buy tickets. We bought all 100 tickets. Now we know that one of our numbers will have to be picked from the box. We are certain of it. Our chances of winning are 1.00 or 100%: ...
maesp 102 probability and random
... b) A man either drives a car or catches a train to go to office each day. He never goes 2 days in a raw by train but if he drives one day, then the next day he is just as likely to drive again as he is to travel by train . Now suppose that on the first day of the week, the man tossed a fair dice and ...
... b) A man either drives a car or catches a train to go to office each day. He never goes 2 days in a raw by train but if he drives one day, then the next day he is just as likely to drive again as he is to travel by train . Now suppose that on the first day of the week, the man tossed a fair dice and ...
- McFarland USD
... example, if a student is selected at random from a class, find the probability that Jane will be selected and the probability that a girl will be selected. b. Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process. For example, find t ...
... example, if a student is selected at random from a class, find the probability that Jane will be selected and the probability that a girl will be selected. b. Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process. For example, find t ...
Problem Set 7
... Give a brief explanation for your answer. (2) Consider a distributed system with n processors. In monitoring the system, we will have each of the n processors in one of 3 states: “running”, “waiting” or “done”. There can be many processes running at the same time. We say that the system is blocked i ...
... Give a brief explanation for your answer. (2) Consider a distributed system with n processors. In monitoring the system, we will have each of the n processors in one of 3 states: “running”, “waiting” or “done”. There can be many processes running at the same time. We say that the system is blocked i ...