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Frequency tables and frequency diagrams

When a lot of 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 .

Example

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.

13816121216
7181116157
111213211719
111410191312
7166141218
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 four groups as shown below. Of course, smaller groups would be more accurate but there may be too many groups to show up any pattern in the data.

Number of customersTallyFrequency
5-10\(\cancel{||||}~|\)6
11-15\(\cancel{||||}~\cancel{||||}~||||\)14
16-20\(\cancel{||||}~||||\)9
21-25\(|\)1
Number of customers5-10
Tally\(\cancel{||||}~|\)
Frequency6
Number of customers11-15
Tally\(\cancel{||||}~\cancel{||||}~||||\)
Frequency14
Number of customers16-20
Tally\(\cancel{||||}~||||\)
Frequency9
Number of customers21-25
Tally\(|\)
Frequency1

Frequency diagrams

A frequency diagram, often called a line chart or a frequency polygon, shows the frequencies for different groups. The frequency chart below shows the results of the table. To plot a frequency polygon of grouped data, plot the frequency at the midpoint of each group.

Number of customers vs frequency graph