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Основно съдържание

STANDARDS

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US-AK

Math

Alaska Math

Statistics and Probability: Interpreting Categorical and Quantitative Data

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

S-ID.1

Mostly covered
Represent data with plots on the real number line (dot plots, histograms, and box plots).

S-ID.2

Fully covered
Use 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.

S-ID.3

Mostly covered
Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). For example: Justify why median price of homes or income is used instead of the mean.

S-ID.4

Fully covered
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.

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

S-ID.5

Mostly covered
Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.

S-ID.6

Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

S-ID.6.a

Partially covered
Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.

S-ID.6.b

Mostly covered
Informally assess the fit of a function by plotting and analyzing residuals. For example: Describe solutions to problems that require interpolation and extrapolation.

S-ID.6.c

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

Interpret linear models.

S-ID.7

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

S-ID.8

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

S-ID.9

Fully covered
Distinguish between correlation and causation.