Cambridge Pre-U Syllabus - Cambridge International Examinations

64
Notes on the use of statistics in Biology
Cambridge Pre-U Draft
Candidates should know the distinction between descriptive statistics and statistical tests. They should also
appreciate the requirement to choose appropriate statistical methods before planning an investigation in
which they will either collect primary data or analyse secondary data. Candidates should have an
understanding of the different types of variable and also the different types of data that they may collect or be
asked to analyse. These are:
Type of variable Type of data
Qualitative
Categoric Nominal
Ordered Ordinal (ranked)
Quantitative
Continuous Interval (having any value, e.g. 1.0, 2.5, etc.)
Discrete Interval (integers only, e.g. 1, 2, 3, etc.)
For quantitative data, candidates should understand the difference between a normal distribution and a
distribution that is non-normal. Candidates should know appropriate descriptive statistical methods to
simplify their data. They should be able to use a calculator and/or spreadsheet program to find the mean,
median, mode, total range, interquartile range, standard deviation, standard error and 95%CI. Standard error
and 95%CI are useful for expressing the reliability of an estimate of the mean and for putting error bars on
graphs. Candidates should understand how to apply these methods and explain their significance for their
own data and any given data.
Candidates should know when it is appropriate to use a statistical test. They should be able to use statistical
tests to test for an association and when to test for the significance of differences between samples. The chisquared
(χ 2 ) test is used to test the difference between observed and expected frequencies of nominal data.
The chi-squared test allows the evaluation of the results of breeding experiments and ecological sampling.
The t-test is of value in much of Biology to test for the significance of differences between samples.
Candidates should be able to use Pearson’s linear correlation to test for a correlation between two sets of
normally-distributed data and Spearman’s rank correlation to test for a correlation between two sets of data
that are not distributed normally. They should know that a correlation does not necessarily imply a causative
relationship. These statistical methods are dealt with fully in many books and web sites on statistics for
Biology.
Candidates are not expected to remember the following equations and symbols. They are expected to be
able to use the equations to calculate standard deviations and standard errors (which they may use for error
bars on graphs), to test for significant differences between the means of two small unpaired samples and to
perform a chi-squared test on suitable data from genetics or ecology. Candidates will be given access to the
equations, the meanings of the symbols, a t-table and a chi-squared table. In both the t-test and the chisquared
test they should be able to calculate the number of degrees of freedom without any reminders. They
should appreciate levels of significance and use calculated (or given) values of t and χ 2 to make appropriate
conclusions.