Statistical Testing
The Concept of Significance
A statistical test is needed to prove if differences during experiments have occurred by chance or
not.
The Concept of Probability
All studies employ a significance level in order to check for significant differences or a relationship.
The accepted level of probability in psychology is 0.05(or 5%). This is the level at which the
researcher decides to accept the research hypothesis or not.
If the experimental hypothesis is accepted, this means there is less than 5% probability that the
results occurred by chance. In simple terms, this means the researcher can be certain that the
difference found was because of the manipulation of the independent variable- but there will always
be a 5% doubt even if significance is found, but there is 95% certainty.
In some circumstances, such as research that may involve a human cost, (new drugs being trialed or
when a particular investigation is a one off or there is no possibility it can be repeated in the future)
researchers need to be even more confident that the results are not due to chance and so employ a
stricter, more stringent significance level such as 0.01. (the 1% level) and there is 99% certainty.
The Critical Value
When the statistical test has been calculated the researcher is left with a number- the calculated
value. This needs to be compared with the critical value to decide whether the result is significant or
not. The critical values for a sign test are given in a table of critical values.
You need the following information to use the table:
The significance level desired (0.05 or 0.01)
The number of participants in the investigation (the N Value)
Whether the hypothesis is directional (one-tailed) or non-directional (two-tailed.)
For the sign test, the calculated value must be equal to or lower than the critical value for the result
to be regarded as significant.
Alternative (Experimental) Hypothesis
Directional (one-tailed) hypothesis: Effect from one variable to another e.g. greater/smaller
difference
Non-Directional (two-tailed) hypothesis: Effect between variables, but do not know which
difference.
The Sign Test
It is used to determine whether the difference we have found is significant. To use the sign test:
1. We need to be looking for a difference rather than an association.
2. We need to have used a repeated measures design.
3. We need data that is nominal.
1
The Concept of Significance
A statistical test is needed to prove if differences during experiments have occurred by chance or
not.
The Concept of Probability
All studies employ a significance level in order to check for significant differences or a relationship.
The accepted level of probability in psychology is 0.05(or 5%). This is the level at which the
researcher decides to accept the research hypothesis or not.
If the experimental hypothesis is accepted, this means there is less than 5% probability that the
results occurred by chance. In simple terms, this means the researcher can be certain that the
difference found was because of the manipulation of the independent variable- but there will always
be a 5% doubt even if significance is found, but there is 95% certainty.
In some circumstances, such as research that may involve a human cost, (new drugs being trialed or
when a particular investigation is a one off or there is no possibility it can be repeated in the future)
researchers need to be even more confident that the results are not due to chance and so employ a
stricter, more stringent significance level such as 0.01. (the 1% level) and there is 99% certainty.
The Critical Value
When the statistical test has been calculated the researcher is left with a number- the calculated
value. This needs to be compared with the critical value to decide whether the result is significant or
not. The critical values for a sign test are given in a table of critical values.
You need the following information to use the table:
The significance level desired (0.05 or 0.01)
The number of participants in the investigation (the N Value)
Whether the hypothesis is directional (one-tailed) or non-directional (two-tailed.)
For the sign test, the calculated value must be equal to or lower than the critical value for the result
to be regarded as significant.
Alternative (Experimental) Hypothesis
Directional (one-tailed) hypothesis: Effect from one variable to another e.g. greater/smaller
difference
Non-Directional (two-tailed) hypothesis: Effect between variables, but do not know which
difference.
The Sign Test
It is used to determine whether the difference we have found is significant. To use the sign test:
1. We need to be looking for a difference rather than an association.
2. We need to have used a repeated measures design.
3. We need data that is nominal.
1
