Common Core · High school
HSS-ID.A.2
High school — Use statistics appropriate to the shape of the data to compare centre (median, mean) and spread (interquartile range, standard deviation) of two or more data sets.
High school — Use statistics appropriate to the shape of the data distribution to compare centre and spread of two or more data sets.
High school — Use statistics appropriate to the shape of the data distribution to compare centre and spread of two or more different data sets.
The 3 skills that cover it
- Standard Deviation & z-scoresMeasure spread with the average squared distance from the mean, and use z-scores to compare values from different data sets.Read the lesson →
- Histograms, Box Plots & ShapeRead a dot plot, a histogram and a box plot, build the five-number summary a box plot is drawn from, describe the shape of a distribution as symmetric or skewed, and compare two distributions by centre and spread.Read the lesson →
- The Normal DistributionUse the bell curve to turn a value into a proportion and back: the empirical rule, z-scores with a table, percentiles, the value behind a percentage, and comparing scores from different distributions.Read the lesson →
What a student should be able to do
- Compute the variance of a small data set from its mean.
- Compute the standard deviation and state it in the units of the data.
- Convert a value to a z-score and read a z-score back into a value.
- Apply the 68-95-99.7 rule to a roughly bell-shaped data set.
- Read counts and totals from a dot plot or a histogram.
- Find the five-number summary of a data set and read a box plot back into it.
- Describe the shape of a distribution and say which summary of centre suits it.
- Compare two distributions by their centres and their spreads.
- Use the empirical rule to find the proportion of a normal distribution within or beyond 1, 2 or 3 standard deviations.
- Convert a value to a z-score and use a table to find the proportion below, above or between values.
- Find the value that sits at a given percentile.
- Compare two values from different normal distributions using z-scores.