Geography Reference
In-Depth Information
Numeracy
The 'quantitative revolution' in geography required the discipline
to adopt an explicitly scientifi c approach, including numerical and
statistical methods, and mathematical modelling, so 'numeracy'
became another necessary skill. Its immediate impact was greatest
on human geography as physical geographers were already
using these methods. A new lexicon encompassing the language
of statistics and its array of techniques entered geography as a
whole. Terms such as random sampling, correlation, regression,
tests of statistical signifi cance, probability, multivariate analysis,
and simulation became part both of research and undergraduate
teaching. Correlation and regression are procedures to measure
the strength and form, respectively, of the relationships between
two or more sets of variables. Signifi cance tests measure the
confi dence that can be placed in those relationships. Multivariate
methods enable the analysis of many variables or factors
simultaneously - an appropriate approach for many complex
geographical data sets. Simulation is often linked to probability
and is a set of techniques capable of extrapolating or projecting
future trends.
This revolution forced new thinking in the discipline and a shift
away from qualitative description, case studies, and the unique
or idiographic, to quantitative measurements, representative
samples, and nomothetic theory with its ability to generalize
and predict. Geographers embraced this new approach and its
associated set of analytical skills with varying levels of expertise.
At one end of the spectrum were the dedicated and innovative
researchers capable of interaction with statisticians, computer
programmers, and mathematicians; at the other were the mass of
students and practitioners more-or-less competent at basic levels
of statistical analysis and the management of data sets.
An interesting demonstration of how numeracy in general,
and multivariate analysis in particular, enables long-standing
