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7.1
The Multiplication Rule for Counting
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The Multiplication Rule for Counting is used to count large sets.
7.2
Permutations
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Using the Multiplication Rule for Counting to enumerate permutations.
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Simplifying and computing expressions involving factorials.
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Using factorials to count permutations.
7.3
Combinations
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Permutations are used to count subsets when order matters; combinations work when order doesn't matter.
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Combinations can also be computed using factorials.
7.4
Tree Diagrams, Tables, and Outcomes
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We identify the sample space of an experiment by identifying all of its possible outcomes.
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Tables can help us find a sample space by keeping the possible outcomes organized.
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Tree diagrams provide a visualization of the sample space of an experiment that involves multiple stages.
7.5
Basic Concepts of Probability
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The theoretical probability of an event is the ratio of the number of equally likely outcomes in the event to the number of equally likely outcomes in the sample space.
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Empirical probabilities are computed by repeating the experiment many times, and then dividing the number of replications that result in the event of interest by the total number of replications.
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Subjective probabilities are assigned based on subjective criteria, usually because the experiment can’t be repeated and the outcomes in the sample space are not equally likely.
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The probability of the complement of an event is found by subtracting the probability of the event from one.
7.6
Probability with Permutations and Combinations
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We use permutations and combinations to count the number of equally likely outcomes in an event and in a sample space, which allows us to compute theoretical probabilities.
7.7
What Are the Odds?
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Odds are computed as the ratio of the probability of an event to the probability of its compliment.
7.8
The Addition Rule for Probability
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The Addition Rule is used to find the probability that one event or another will occur when those events are mutually exclusive.
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The Inclusion/Exclusion Principle is used to find probabilities when events are not mutually exclusive.
7.9
Conditional Probability and the Multiplication Rule
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Conditional probabilities are computed under the assumption that the condition has already occurred.
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The Multiplication Rule for Probability is used to find the probability that two events occur in sequence.
7.10
The Binomial Distribution
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Binomial experiments result when we count the number of successful outcomes in a fixed number of repeated, independent trials with a constant probability of success.
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The binomial distribution is used to find probabilities associated with binomial experiments.
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Probability density functions (PDFs) describe the probabilities of individual outcomes in an experiment; cumulative distribution functions (CDFs) give the probabilities of ranges of outcomes.
7.11
Expected Value
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The expected value of an experiment is the sum of the products of the numerical outcomes of an experiment with their corresponding probabilities.
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The expected value of an experiment is the most likely value of the average of a large number of replications of the experiment.