The release of mortality statistics related to sickness and disability benefits has caused fierce debate about what the figures actually mean. It has to be said that the way the figures were presented – in a flat descriptive way – makes drawing causal links and inferences very difficult and making useful comparisons impossible. This of course was intentional.
There’s a simple difference between descriptive and inferential statistics – descriptive statistics simply summarise a current dataset, it’s just raw data. Subsequently, analysis is limited to the data and does not provide a scope that permits the extrapolation of any conclusions about a group or population. Inferential statistics are usually used to test an hypothesis, and aim to draw conclusions about an additional population outside of the dataset. Inferential statistics allow researchers to make well-reasoned inferences about the populations in question, and may be tested for validity and reliability, using various appropriate…
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Christopher John Ball 
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