# Standards

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### CCSS.Math.Content.HSS-CP.A.3

Understand the conditional probability of A given B as P(A and B)/P(B), and interpret independence of A and B as saying that the conditional probability of A given B is the same

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### CCSS.Math.Content.HSS-CP.A.4

Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. For

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### CCSS.Math.Content.HSS-CP.A.5

Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations. For example, compare the chance of having lung cancer if you are a smoker with the chance of being a smoker if you have lung c

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### CCSS.Math.Content.HSS-CP.B.6

Find the conditional probability of A given B as the fraction of B’s outcomes that also belong to A, and interpret the answer in terms of the model.

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### CCSS.Math.Content.HSS-CP.B.7

Apply the Addition Rule, P(A or B) = P(A) + P(B) – P(A and B), and interpret the answer in terms of the model.

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### CCSS.Math.Content.HSS-CP.B.8

(+) Apply the general Multiplication Rule in a uniform probability model, P(A and B) = P(A)P(B|A) = P(B)P(A|B), and interpret the answer in terms of the model.

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### CCSS.Math.Content.HSS-CP.B.9

(+) Use permutations and combinations to compute probabilities of compound events and solve problems.

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### CCSS.Math.Content.HSS-MD.A.1

(+) Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; graph the corresponding probability distribution using the same graphical displays as for data distributions.

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### CCSS.Math.Content.HSS-MD.A.2

(+) Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.

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### CCSS.Math.Content.HSS-MD.A.3

(+) Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value. For example, find the theoretical probability distribution for the number of correct

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### CCSS.Math.Content.HSS-MD.A.4

(+) Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value. For example, find a current data distribution on the number of TV sets per household in th

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### CCSS.Math.Content.HSS-MD.B.5

(+) Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values.

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