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Основно съдържание

STANDARDS

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US-ND

Math

North Dakota Math

High School—Statistics and Probability: Interpreting Categorical and Quantitative Data

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

HS.S-ID.1

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

HS.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.

HS.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).

HS.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, or tables to estimate areas under the normal curve.

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

HS.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.

HS.S-ID.6

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

HS.S-ID.6.a

Partially covered
Fit a function to the data (with or without technology). Use functions fitted to data to solve problems in the context of the data.

HS.S-ID.6.b

Mostly covered
(+) Informally assess the fit of a function by plotting and analyzing residuals.

Interpret linear models

HS.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. Interpolate and extrapolate the linear model to predict values.

HS.S-ID.8

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

HS.S-ID.9

Fully covered
Distinguish between correlation and causation.