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Data is statistically significant if the p (probability) value is below a certain level (ex: 5% or 1%). The p value describes how often one would receive the results they got if left to chance alone. The lower the p value, the less likely it is that your results were due to chance and is stronger evidence against the null hypothesis. Also important to keep in mind is that just because something is statistically significant does not mean it is practically significant.
A high F statistic would results in a lower Sig, or P value, which would indicate that your results are significant.
The P value is caluated through the SIG figure within your anova. Anything less than 0.05 is classed as significant in your study. Julie Pallants SPSS survival Manual is a great resource for this if you need further assistance. Aimee The P value is caluated through the SIG figure within your anova. Anything less than 0.05 is classed as significant in your study. Julie Pallants SPSS survival Manual is a great resource for this if you need further assistance. Aimee
Normally you would find the critical value when given the p value and the test statistic.
Statistically significant is the term used to define when two data are distinct enough in value as to be considered different values. To determine whether two data are close enough in value or distinct enough in value to be considered the same or different, usually you have to do a p-test or a t-test, depending on the type of data that you are looking at. Then confer with the corresponding chart for the test that you did to see whether or not the data is statistically significant.