
Sec. 6.3 Part 2 Blank Notes
... The multiplication rule says that the probability of reaching the end of any complete branch is the product of the probabilities written on its segments. ...
... The multiplication rule says that the probability of reaching the end of any complete branch is the product of the probabilities written on its segments. ...
3.3-guided-notes - Bryant Middle School
... 1) Event A: Randomly select a jack from a standard deck of cards. Event B: Randomly select a face card from a standard deck of cards. ...
... 1) Event A: Randomly select a jack from a standard deck of cards. Event B: Randomly select a face card from a standard deck of cards. ...
Math 160 Professor Busken Chapter 6 Worksheet Name: Use Table
... 10. The amount of coffee dispensed by a drink vending machine is normally distributed with a mean of 12.0 oz and a standard deviation of .44 oz. What is the probability that a randomly selected cup of coffee has more than 12.5 oz.? ...
... 10. The amount of coffee dispensed by a drink vending machine is normally distributed with a mean of 12.0 oz and a standard deviation of .44 oz. What is the probability that a randomly selected cup of coffee has more than 12.5 oz.? ...
Section 5.1 Introduction to Probability and
... if I toss the coin 10 times, I should get 5 Heads. However, with such a small number of tosses there is a lot of room for variability. There ...
... if I toss the coin 10 times, I should get 5 Heads. However, with such a small number of tosses there is a lot of room for variability. There ...
an elementary proof
... A00, A01 , . . . , A0ν is another intersection system such that B ⊆ A0ν , we can form an intersection system A000 , A001 , . . . , A00m by taking consecutively A00m = An ∩ A0ν , A00m−1 = An−1 ∩ A0ν−1 , . . . , identifying A000 with the first set with cardinality 1 obtained in this process. As a resu ...
... A00, A01 , . . . , A0ν is another intersection system such that B ⊆ A0ν , we can form an intersection system A000 , A001 , . . . , A00m by taking consecutively A00m = An ∩ A0ν , A00m−1 = An−1 ∩ A0ν−1 , . . . , identifying A000 with the first set with cardinality 1 obtained in this process. As a resu ...
Homework due 09/15 1. Consider a sequence of five Bernoulli trials
... 1. Consider a sequence of five Bernoulli trials. Let X be the number of times that a head is followed immediately by a tail. For example, if the outcome is ω = HHT HT then X(ω) = 2 since a head is followed directly by a tail at trials 2 and 3, and also at trials 4 and 5. Find the probability mass fu ...
... 1. Consider a sequence of five Bernoulli trials. Let X be the number of times that a head is followed immediately by a tail. For example, if the outcome is ω = HHT HT then X(ω) = 2 since a head is followed directly by a tail at trials 2 and 3, and also at trials 4 and 5. Find the probability mass fu ...
Probability Unit
... In a monthly report, the local animal shelter states that it currently has 24 dogs and 18 cats available for adoption. Eight of the dogs and 6 of the cats are male. Find each of the following conditional probabilities if an animal is selected at random: a. ...
... In a monthly report, the local animal shelter states that it currently has 24 dogs and 18 cats available for adoption. Eight of the dogs and 6 of the cats are male. Find each of the following conditional probabilities if an animal is selected at random: a. ...
K.K. Gan Physics 416 Problem Set 2 Due April 18, 2011
... pass through a square with an area of 1 m2 each µsec. Inside the square is a neutrino detector with an area of 1 mm2. Assume Poisson statistics for this problem. a) What is the average number of neutrinos going through the detector each µsec? b) What is the probability that no neutrinos go through t ...
... pass through a square with an area of 1 m2 each µsec. Inside the square is a neutrino detector with an area of 1 mm2. Assume Poisson statistics for this problem. a) What is the average number of neutrinos going through the detector each µsec? b) What is the probability that no neutrinos go through t ...
Math 1312 – test II – Review
... A sample of 20 employees indicates that 12 have a college degree and 8 do not. If a person has a college degree, they have a probability of 0.7 of being happy at the workplace. If a person does not have a college degree, then they have a probability of 0.4 of being happy at the workplace. A person i ...
... A sample of 20 employees indicates that 12 have a college degree and 8 do not. If a person has a college degree, they have a probability of 0.7 of being happy at the workplace. If a person does not have a college degree, then they have a probability of 0.4 of being happy at the workplace. A person i ...
Infinite monkey theorem

The infinite monkey theorem states that a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type a given text, such as the complete works of William Shakespeare.In this context, ""almost surely"" is a mathematical term with a precise meaning, and the ""monkey"" is not an actual monkey, but a metaphor for an abstract device that produces an endless random sequence of letters and symbols. One of the earliest instances of the use of the ""monkey metaphor"" is that of French mathematician Émile Borel in 1913, but the first instance may be even earlier. The relevance of the theorem is questionable—the probability of a universe full of monkeys typing a complete work such as Shakespeare's Hamlet is so tiny that the chance of it occurring during a period of time hundreds of thousands of orders of magnitude longer than the age of the universe is extremely low (but technically not zero). It should also be noted that real monkeys don't produce uniformly random output, which means that an actual monkey hitting keys for an infinite amount of time has no statistical certainty of ever producing any given text.Variants of the theorem include multiple and even infinitely many typists, and the target text varies between an entire library and a single sentence. The history of these statements can be traced back to Aristotle's On Generation and Corruption and Cicero's De natura deorum (On the Nature of the Gods), through Blaise Pascal and Jonathan Swift, and finally to modern statements with their iconic simians and typewriters. In the early 20th century, Émile Borel and Arthur Eddington used the theorem to illustrate the timescales implicit in the foundations of statistical mechanics.