Common Core State

HSS.IC.B6

Evaluate reports based on data.

October 1, 2018
HSS.ID.A1

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

October 1, 2018
HSS.ID.A2

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.

October 1, 2018
HSS.ID.A3

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

October 1, 2018
HSS.ID.A4

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.

October 1, 2018
HSS.ID.B5

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.

October 1, 2018
HSS.ID.B6

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

October 1, 2018
HSS.ID.B6a

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.

October 1, 2018
HSN.VM.B5a

Represent scalar multiplication graphically by scaling vectors and possibly reversing their direction; perform scalar multiplication component-wise, e.g., as c(vx, vy) = (cvx, cvy).

October 1, 2018
HSN.VM.B5b

Compute the magnitude of a scalar multiple cv using ||cv|| = |c|v. Compute the direction of cv knowing that when |c|v ≠ 0, the direction of cv is either along v (for c > 0) or against v (for c < 0).

October 1, 2018
HSN.VM.C6

(+) Use matrices to represent and manipulate data, e.g., to represent payoffs or incidence relationships in a network.

October 1, 2018
HSN.VM.C7

(+) Multiply matrices by scalars to produce new matrices, e.g., as when all of the payoffs in a game are doubled.

October 1, 2018