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Inter-quartile range, cumulative frequency, box and whisker plots - Higher

If you are studying the higher paper you will need to know the difference between discrete and continuous data, how to plot and interpret histograms, how to calculate inter-quartile ranges, cumulative frequency and box and whisker plots.

Discrete and continuous data

Raw data is the information we get when we do a survey. For example, we might have a list of heights or shoe sizes.

Data can either be discrete or continuous.

Discrete data

This data set shows a group of discrete data.

This is called discrete data because the units of measurement (for example, CDs) cannot be split up; there is nothing between 1 CD and 2 CDs.

Bitesize CD store 31 January 2008

Music formatNumber sold
CD albums140
CD singles70
Total sales270

Shoe sizes are a classic example of discrete data, because sizes 39 and 40 mean something, but size 39.2, for example, does not.

Continuous data

The data set shows a group of continuous data.

This data is called continuous because the scale of measurement - distance - has meaning at all points between the numbers given, eg we can travel a distance of 1.2 and 1.85 and even 1.632 miles.

Continuous data can be shown on a number line, and all points on the line have meaning and are different, but with discrete data only certain values have meaning.

Length of journey to work

Distance in miles0.1 0.2 0.6 1.1 1.2 1.8 2.0 2.7 3.4 4.6 6.2 8.0 12.1 14.2

For each question decide whether the datat set is discrete or continuous.


The heights of pupils in class 3A.

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Height is continuous. For example, a pupil could be 152.3cm.


The number of chocolates in various 500g boxes.

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The number of chocolates is discrete. There would not be half chocolates in a box.

athletes running

The times taken for athletes to run 100m.

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Time is continuous. For example, an athlete may run 100m in 10.37 seconds.

Back to Statistics and probability index

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