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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 format | Number sold |
|---|---|
| CD albums | 140 |
| CD singles | 70 |
| Downloads | 55 |
| Vinyl | 5 |
| Total sales | 270 |
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 1.8 miles.
Length of journey to work
| Distance in miles | 0.1 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.
- Question
The heights of pupils in class 3A.
- Answer
Height is continuous. For example, a pupil could be 152.3cm.
- Question
The number of chocolates in various 500g boxes.
- Answer
The number of chocolates is discrete. There would not be half chocolates in a box.
- Question
The times taken for athletes to run 100m.
- Answer
Time is continuous. For example, an athlete may run 100m in 10.37 seconds.
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