Mi Math Standards


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HSS-ID.B.6b

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

Informally assess the fit of a function by plotting and analyzing residuals.

Grade levels
09, 10, 11, 12


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HSS-ID.B.6c

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

Fit a linear function for a scatter plot that suggests a linear association.

Grade levels
09, 10, 11, 12


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HSS-ID.C.7

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

Grade levels
09, 10, 11, 12


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HSS-ID.C.8

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

Compute (using technology) and interpret the correlation coefficient of a linear fit.

Grade levels
09, 10, 11, 12


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HSS-ID.C.9

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

Distinguish between correlation and causation.

Grade levels
09, 10, 11, 12


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HSS-MD.A.1

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

(+) 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.

Grade levels
09, 10, 11, 12


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HSS-MD.A.2

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

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

Grade levels
09, 10, 11, 12


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HSS-MD.A.3

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

(+) 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 answers obtained by guessing on all five questions of a multiple-choice test where each question has four choices, and find the expected grade under various grading schemes.

Grade levels
09, 10, 11, 12


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HSS-MD.A.4

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

(+) 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 the United States, and calculate the expected number of sets per household. How many TV sets would you expect to find in 100 randomly selected households?

Grade levels
09, 10, 11, 12


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HSS-MD.B.5

by Troy Patterson - Monday, July 31, 2017, 1:50 PM
 

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

Grade levels
09, 10, 11, 12



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