Data is represented in many different forms. Businesses and the media often use bar charts, pie charts and time series graphs to make information easier to digest.
When a lot of data needs to be sorted, one of the most efficient ways is to use a frequency table.
It is important to consider the sizes of groups when sorting data into a frequency table.
Megan owns a bakery. She counts the number of customers she has each day at lunchtime on 30 consecutive days. The results are shown here.
| 13 | 8 | 16 | 12 | 12 | 16 |
| 7 | 18 | 11 | 16 | 15 | 7 |
| 11 | 12 | 13 | 21 | 17 | 19 |
| 11 | 14 | 10 | 19 | 13 | 12 |
| 7 | 16 | 6 | 14 | 12 | 18 |
Using this data in list form could be time consuming and with a large set of data it may lead to mistakes or miscalculations. A grouped frequency table would help to display and give an overview of the data. The smallest number is 6 and the biggest number is 21, so groups that have a width of 5 are reasonable - this will give a reasonable amount of groups to work with, and the smaller the groups, the more accurate the analysis will be.
| Number of customers | Tally | Frequency |
|---|---|---|
| 5-10 | \[\cancel{||||}~|\] | 6 |
| 11-15 | \[\cancel{||||}~\cancel{||||}~||||\] | 14 |
| 16-20 | \[\cancel{||||}~||||\] | 9 |
| 21-25 | \[|\] | 1 |