Statistics for the Terrified: Glossary
Click on an item below to see the definition
Economic significance (relevance):
Getting statistical significance is not necessarily the end of the story. In an
economics study you would also want to see economic significance, which is not always present. In economic terms, the
statistically significant difference may be so small as to be irrelevant. Note that we may see economic significance in
a sample, but we cannot conclude that this is a real effect in the population unless we also have statistical significance.
A new management practice that increases profits by 38p per year has no economic value.
Educational significance:
Getting statistical significance is not necessarily the end of the story. In an
educational study you would also want to see educational significance, which is not always present. In educational terms, the
statistically significant difference may be so small as to be irrelevant. Note that we may see educational significance in
a sample, but we cannot conclude that this is a real effect in the population unless we also have statistical significance.
If an expensive new teaching method increases reading ability by 0.02% in a nationwide study, it has no educational significance.
Error:
A misleading term: there is no mistake. This is actually the natural variation occurring in a sample.
Estimation:
A set of techniques where the value of a population parameter is inferred
from sample data.
Expected values:
The values you would expect to get in a classification table if the null hypothesis
were true.
Exploratory analyses:
This is a kind of getting-to-know-your-data exercise that is carried out at the
beginning of the analysis.
For the complete glossary, buy the interactive tutorial -
