It means, within the laws of statistical analysis, that the statistic occurs more frequently than the baseline number which is considered "random" for the particular application. It happens more frequently than "random" - hence there is, or may be, something "significant" about that.
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A high F statistic would results in a lower Sig, or P value, which would indicate that your results are significant.
The F statistic is statistic which may be used to test whether a regression accounts for a statistically significant proportion of the observed variation in the dependent variable.
the populations have an excess of heterozygotes
You make assumptions about the nature of the distribution for a set of observations and determine a pair of competing hypotheses - a null hypotheis and an alternative. Based on the null hypothesis you devise a test for a statistic that is based on the observations. Assuming the null hypothesis is true, if the probability of observing a test statistic that is at least as extreme as the one obtained is smaller than some pre-determined level (that is, if the observations are very unlikely under the null hypothesis) then the result is said to be statistically significant. This does not automatically imply managerial significance since, among other factors, the latter must take account of the consequences (costs) of making the wrong decision.
You can calculate a result that is somehow related to the mean, based on the data available. Provided that you can work out its distribution under the null hypothesis against appropriate alternatives, you have a test statistic.