Introduction
This topic covers how raw observations are organised into a frequency distribution, how continuous data are grouped into classes, and which graphical summaries (bar chart, histogram, frequency polygon, cumulative curve) present the distribution clearly. It is the descriptive step that comes before measures of central tendency and spread.
Frequency distribution
A frequency distribution shows how often each value, or each class of values, occurs in a data set of size n. Its main quantities are:
- Absolute frequency n_i: the number of observations in category or class i.
- Relative frequency f_i: the proportion of all observations in that class, usually also given as a percentage. The relative frequencies always sum to 1 (or 100%).
- Cumulative frequency: the running total of absolute frequencies up to and including a class. It answers questions such as how many patients had a value below a given limit.
Example: systolic blood pressure measured in 60 patients, grouped into 10 mmHg classes.