Cluster: Investigate patterns of association in bivariate data

Standard: Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.

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Not Rated
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Cluster: Investigate patterns of association in bivariate data

Standard: Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.

Degree of Alignment:
Not Rated
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Cluster: Investigate patterns of association in bivariate data

Standard: Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.

Degree of Alignment:
Not Rated
(0 users)

Learning Domain: Statistics and Probability

Standard: Investigate patterns of association in bivariate data

Indicator: Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.

Degree of Alignment:
Not Rated
(0 users)

Learning Domain: Statistics and Probability

Standard: Investigate patterns of association in bivariate data

Indicator: Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.

Degree of Alignment:
Not Rated
(0 users)

Learning Domain: Statistics and Probability

Standard: Investigate patterns of association in bivariate data

Indicator: Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.

Degree of Alignment:
Not Rated
(0 users)

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