Representing data

Data can be represented in many ways such as using bar charts, pie charts and frequency diagrams.

A frequency table is a great way to organise data.

Mass (Kg)TallyFrequency
41 – 49///3
50 – 58//// /6
59 – 67////5
68 – 76//// /6
77 – 85//2

This information can then be represented into a frequency diagram/polygon. To plot the frequency of grouped data (as shown above), you have to find the midpoints of the group and plot those.

Below shows a frequency diagram:

A bar chart also shows the frequency of events occurring. Note: the height of the bar shows the frequency.

A pie chart is a chart that uses a circle. Remember a circle = 360</span>°.

To draw a pie chart: once you have the frequencies, divide the frequency by the total and multiply it by 360. This provides you with the angle that you need to draw on the pie chart.

A pictogram is another way of representing data but uses pictures to show the event frequency. Note: a key is necessary to show what each picture represents.

A scatter graph shows the correlation between variables.

There can be positive, negative or no correlation.

Positive correlation: when one variable increases, the other also increases.

Negative correlation: when one variable increases, the other decreases.

No correlation: no relationship.

It is important to note that correlation does not mean causation. If two variables have a correlation, it does not mean that one of them causes the other to occur.

Once scatter graphs are formed, a line is drawn through most of the points. This is called the line of best fit.

Sometimes you may have to extrapolate the data. Look at the diagram below, if we wanted to find out the number of umbrellas sold when the rainfall is 7mm. We have to extend the line of best fit to do this.