By continuous data we mean that data have been quantified in some wax I:
accuracy will be dependent on the precision with which it has been measure
For example we may have used the Lowry method to determine tllfl amount 0
protein in a given sample.We may then report its protein content but the
number of decimal places that we would choose to use to report the value is
dependent on the precision of the analytical technique.
With discrete data we are dealing with exact numbers usually determined
by a counting method This could be the number of petals on a flower heart
rate or cells counted using a haemocytometer In each case we are dealing with
exact numbers so we would have 6 petals 60 heartbeats per minute or 12 cells
in a grid.
In each of these two examples data is numerical and has been measured or
counted and therefore has definitive values These data are also known as
interval data.
The statistical tests that are applied to interval data are the Z-test and the
Student Latest.
Not all data generated in an experiment is precise in this way Sometimes we
may need to consider variables more difficult to quantify such as an emotional
response or the severity of a discasc.This type of variable cannot be measured
accurately this type of data is known as ordinal data Statistical tests that may
be applied to ordinal data are the Mann—V hitney Uetcst or the Wilcoxon
signed rank test.
In certain experiments we may need to collect inforniation that is descrip.
iivc about the subjects in our iiwcstigation.V herc data are descriptive WC
tend to summari c the inforination by placing it into different categories.
Examples of categorical data include eye or hair colour spccics within 1 gciiiis,
or male/female subjects Data that are categorical are also known as noininal
data.The Cl-ii-squared test is applied to daitzi at the iimiiiiul level.