probability and significance

• statistical test is not significant

  The null hypothesis states there is no difference or no correlation between the conditions. The statistical test determines which we accept and reject. Probability is a measure of the likelihood that a particular event will occur, where 0 is a statistical impossibility and 1 a statistical certainty. There are no statistical certainties in psychology but there is a significance level - the point at which the null hypothesis is accepted or rejected.
• Use of statistical tables

  To check for statistical significance the calculated value is compared with a critical value in a table of critical values based on probabilities.

  To find the correct critical value, there are three criteria : Hypothesis one tailed or two ?, Number of participants or degree of freedom, level of significance. This means there is a 5% chance the result of a particular study sample occured even if there was no real difference in the population. Sometimes a more stringent level is used for studies like drug trials.
• Type 1 errors

  The null hypothesis is rejeceted and the alternative hypothesis is accepted when the null hypothesis was infact true. This is an optimistic error or false positive as a significant difference or correlation is found when one does not exist

  This is more likely to occur if the significance level is too lenient (too high e.g. 10%)
• Type 2 errors

  The null hypothesis is accepted and the alternative hypothesis is rejected when the alternative was true. This is a pessimistic error or false negative.

  This is more likely to occur if the significance level is too stringent ( too low like 1%), as potentially significant values may be missed