Geography Reference
In-Depth Information
3
Key concepts 2
Statistics
Introduction
3.1
h is chapter is concerned with ways of summarizing and exploring numerical data.
Even a brief summary of the key principles of statistics would require a dedicated
topic, so the intention of this chapter is to introduce some (very selective) ideas that it
is necessary to understand to make use of parts of the rest of this topic. h ese methods
provide the basis of the
spatial
statistical methods that will be dei ned later on. h e
analysis of aspatial data (data with no spatial locational information) and spatial data
usually starts with computation of standard summary statistics, as described in this
chapter. Statistics can be divided into descriptive statistics, which provide summaries,
and inferential statistics, which allow the making of inferences about a population
(a complete data set representing all cases, e.g. all people in a country) from a sample.
A sample is a partial data set, such as a population data set which excludes some people
for some reason such as cost limitations, enabling only a limited survey. Both descriptive
statistics and inferential statistics are introduced in this chapter, although more space
is devoted to the former. Core concepts, which will be discussed in Section 3.4, include
probabilities and the signii cance level. A statistical hypothesis may be associated with
a probability that it is true or false and this is a central notion in statistics.
h e following sections consider the purpose of statistical methods and introduce
some ways of describing data sets. h e focus here is initially on univariate statistics—
methods that are used to analyse only one variable. Next, the focus is on multivariate
methods—methods that deal with two or more variables simultaneously. In addition
to introducing methods, the chapter will introduce some of the principles of statistical
notation, for example one concern is to demonstrate how to 'read' the equations given
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