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Ch. 3 - Probability
Larson - Elementary Statistics: Picturing the World 8th Edition
Larson8th EditionElementary Statistics: Picturing the WorldISBN: 9780137493470Not the one you use?Change textbook
Chapter 3, Problem 3.2.34

"According to Bayes’ Theorem, the probability of event A , given that event B has occurred, is
P(A|B) = P(A) * P(B|A)P(A) * P(B|A) + P(A') * P(B|A').
In Exercises 33–38, use Bayes’ Theorem to find P(A|B).
34. P(A) = 3/8, P(A') = 5/8, P(B|A) = 2/3 , and P(B|A') = 3/5 "

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1
Step 1: Recall Bayes' Theorem formula: P(A|B) = (P(A) * P(B|A)) / (P(A) * P(B|A) + P(A') * P(B|A')). This formula helps calculate the conditional probability of event A given that event B has occurred.
Step 2: Substitute the given values into the formula. From the problem, P(A) = 3/8, P(A') = 5/8, P(B|A) = 2/3, and P(B|A') = 3/5. Replace these values in the formula.
Step 3: Calculate the numerator of the formula, which is P(A) * P(B|A). Multiply 3/8 by 2/3.
Step 4: Calculate the denominator of the formula, which is P(A) * P(B|A) + P(A') * P(B|A'). First, calculate P(A') * P(B|A') by multiplying 5/8 by 3/5. Then, add this result to the numerator calculated in Step 3.
Step 5: Divide the numerator (from Step 3) by the denominator (from Step 4) to find P(A|B). This will give you the conditional probability of event A given that event B has occurred.

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Bayes' Theorem

Bayes' Theorem is a fundamental principle in probability theory that describes how to update the probability of a hypothesis based on new evidence. It states that the probability of event A given event B, denoted as P(A|B), can be calculated using the formula P(A|B) = P(A) * P(B|A) / P(B). This theorem is particularly useful in scenarios where we want to revise our beliefs in light of new data.
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Conditional Probability

Conditional probability is the probability of an event occurring given that another event has already occurred. It is denoted as P(A|B), which represents the probability of A occurring under the condition that B is true. Understanding conditional probability is crucial for applying Bayes' Theorem, as it allows us to assess how the occurrence of one event influences the likelihood of another.
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Prior and Posterior Probabilities

In the context of Bayes' Theorem, prior probability refers to the initial assessment of the likelihood of an event before considering new evidence, denoted as P(A). Posterior probability, on the other hand, is the updated probability after taking into account the new evidence, represented as P(A|B). Distinguishing between these two types of probabilities is essential for understanding how new information can alter our beliefs about uncertain events.
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Related Practice
Textbook Question

97. Rolling a Pair of Dice You roll a pair of six-sided dice and record the sum.

a. List all of the possible sums and determine the probability of rolling each sum.

b. Use technology to simulate rolling a pair of dice and record the sum 100 times. Make a tally of the 100 sums and use these results to list the probability of rolling

each sum.

c. Compare the probabilities in part (a) with the probabilities in part (b). Explain any similarities or differences.

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Textbook Question

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47. You choose nine music listeners at random. What is the probability that none of them say their primary source for new music is friends or social media?

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Textbook Question

Using the Fundamental Counting Principle In Exercises 37-40, use the Fundamental Counting Principle.

40. True or False Quiz Assuming that no questions are left unanswered, in how many ways can a six-question true or false quiz be answered?

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Textbook Question

True or False? In Exercises 3-6, determine whether the statement is true or false. If it is false, rewrite it as a true statement.

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Textbook Question

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Textbook Question

16. Can Defects Of the cans produced by a company, 96% do not have a puncture, 93% do not have a smashed edge, and 89.3% have neither a puncture nor a smashed edge. Find

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