7.4.2 Probability & Errors

Statistical tests work based on probability rather than uncertainty. All statistical tests employ a significance level (the point at which a researcher can claim to have found a significant difference or correlation within the data). The usual level of significance in psychology is 0.05 (or 5%) – written as p<0.05 (where p is probability).

Critical Value – the value that acts as the 'cut-off' point where a psychologist can decide to accept or reject the null hypothesis (found on table of critical values). Once a statistical test has been calculated the result is called the calculated or observed value. The check for statistical significance, the calculated value is compared with the critical value.

To use a table of critical values, there are three criteria:

• A one-tailed test is used when the hypothesis is directional, or a two-tailed test is used if the hypothesis is non-directional.
• The number of participants in the study – the N value. For some tests, degrees of freedom (df) are calculated instead.
• The level of significance (or p value): 0.05

Type I and Type II Errors

Type I – when null hypothesis is rejected, and the alternative hypothesis is accepted when it should have been the other way around because in reality the null hypothesis is true. Often referred to as a false positive as researcher claims to have found a significant difference when one does not exist.

Type II – when null hypothesis is accepted but should have been the alternative hypothesis is true, because in reality the null hypothesis is true. Often referred to as a false negative.