NC.M1.S-ID

Statistics and Probability: Interpreting Categorical and Quantitative Data

NC.M1.S-ID.1Use technology to represent data with plots on the real number line (histograms, and box plots).NC.M1.S-ID.2Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets. Interpret differences in shape, center, and spread in the context of the data sets.NC.M1.S-ID.3Examine the effects of extreme data points (outliers) on shape, center, and/or spread.NC.M1.S-ID.6Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.NC.M1.S-ID.6aFit a least squares regression line to linear data using technology. Use the fitted function to solve problems.NC.M1.S-ID.6bAssess the fit of a linear function by analyzing residuals.NC.M1.S-ID.6cFit a function to exponential data using technology. Use the fitted function to solve problems.NC.M1.S-ID.7Interpret in context the rate of change and the intercept of a linear model. Use the linear model to interpolate and extrapolate predicted values. Assess the validity of a predicted value.NC.M1.S-ID.8Analyze patterns and describe relationships between two variables in context. Using technology, determine the correlation coefficient of bivariate data and interpret it as a measure of the strength and direction of a linear relationship. Use a scatter plot, correlation coefficient, and a residual plot to determine the appropriateness of using a linear function to model a relationship between two variables.NC.M1.S-ID.9Distinguish between association and causation.
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