term significance when related to research has a
very specific role.
Significance refers to the level of certainty
in the results of a study.
We can say that our subjects differed by an
average of ten points with 100% certainty because we
personally witnessed this difference.
To say that the population will differ is
To do this, we must determine how valid our
results are based on a statistical degree of error.
If we find, through the use of inferential
statistics, that the grades of those with and
without work experience are different me must state
the estimated error involved in this inference.
While the standard acceptable error is 5%, it
can be as high as 20% or as low as 0.1%.
amount of error to be accepted in any study must be
determined prior to beginning the study.
In other words, if we want to be 95%
confident in our results, we set the significance
level at .05 (or 5%).
If we want to be 99% confident, our
significance level is set at .01.
We can then state that there is a difference
in the population means at the 95% significance
level or at the 99% significance level if our
statistics support this statement.
If our statistics estimate that there is 10%
error and we said we would accept only 5%, the
results of our study would be stated as not
When determining significance, we are saying
that a difference exists within our acceptable level
of error and we must therefore reject the null
When results are found to be not significant,
the only option available is to accept the null