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Contenido principal

STANDARDS

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US-KY

Math

Kentucky Math

Conceptual Category Statistics and Probability: Statistics and Probability—Interpreting Categorical and Quantitative Data

Cluster: Summarize, represent and interpret data on a single count or measurement variable.

HS.SP.1

Mostly covered
Represent the distribution of data with plots on the real number line (stem plots, dot plots, histograms and box plots). (MP.4, MP.5)

HS.SP.2

Fully covered
Use statistics appropriate to the shape of the numerical data distribution to compare center (median, mean) and spread (interquartile range when comparing medians and standard deviation when comparing means) of different data distributions. (MP.2, MP.6)

HS.SP.3

Mostly covered
Interpret differences in shape, center and spread in the context of the distributions of the numerical data, accounting for the presence and possible effects of extreme data points (outliers). (MP.1, MP.7)

HS.SP.4(+)

Fully covered
When appropriate, fit a normal distribution to a numerical data set for given mean and standard deviation and then estimate population percentages using the Empirical Rule and recognize that there are data sets for which such a procedure is not appropriate. (MP.1, MP.3)

Cluster: Summarize, represent and interpret data on two categorical and quantitative variables.

HS.SP.5

Mostly covered
Summarize categorical data for two or more categories in frequency tables. Calculate and interpret joint, marginal and conditional relative frequencies (probabilities) in the context of the data, recognizing possible associations and trends in the data. (MP.2, MP.7)

HS.SP.6

Represent data on two quantitative variables on a scatter plot and describe how the explanatory and response variables are related. (MP.3, MP.4, MP.5)

HS.SP.6.a

Partially covered
Calculate an appropriate mathematical model, or use a given mathematical model, for data to solve problems in context.

HS.SP.6.b

Partially covered
Informally assess the fit of a model (through calculating correlation for linear data, plotting, calculating and/or analyzing residuals).

Cluster: Interpret linear models.

HS.SP.7

Fully covered
Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. (MP.1, MP.2)

HS.SP.8

Understand the role and purpose of correlation in linear regression. (MP.5, MP.6)

HS.SP.8.a

Fully covered
Use technology to compute correlation coefficient of a linear fit.

HS.SP.8.b

Not covered
Interpret the meaning of the correlation within the context of the data.
(Content unavailable)

HS.SP.8.c

Fully covered
Describe the limitations of correlation when establishing causation.