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.
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.
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.
|Music format||Number sold|
Shoe sizes are a classic example of discrete data, because sizes 39 and 40 mean something, but size 39.2, for example, does not.
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.
|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.
The heights of pupils in class 3A.
Height is continuous. For example, a pupil could be 152.3cm.
The number of chocolates in various 500g boxes.
The number of chocolates is discrete. There would not be half chocolates in a box.