Key Concepts

• The levels of measurement for data are (from lowest to highest): nominal (categorical), ordinal, interval, and ratio.
• Frequency tables group data by how often particular data values occur. The frequency tables can include relative frequencies and cumulative relative frequencies to help draw conclusions about a distribution.

Glossary

cumulative relative frequency: an ordered set of observations from smallest to largest. The cumulative relative frequency is the sum of the relative frequencies for all values that are less than or equal to the given value.

frequency: the number of times a value of the data occurs

interval data: numerical, and allows comparisons by subtracting values. For example, 10 degrees difference in temperatures would be an interval comparison.

levels of measurement: the way a set of data is measured. The four levels of measurement are nominal (categorical), ordinal, interval, and ratio.

nominal scale: qualitative data that includes categories. For example, colors, names, labels, and favorite foods along with yes or no responses would be nominal.

ordinal data: like categorical data, but has a specific order. For example, Excellent, Good, Fair, Poor would be ordinal.

ratio data: numerical, allows for comparisons in ratios. For example, twice as tall would mean heights are ratio data.

relative frequency: the ratio of the number of times a value of the data occurs in the set of all outcomes to the number of all outcomes to the total number of outcomes