Significance tests
Significance is often given as a p value where the p value is the probability of getting a result which is as extreme by chance if the null hypothesis was true (that there is no difference/correlation between 2 groups). For example if I wanted to see whether tomatoes grown in the open vs in the green house had different sizes, the null hypothesis would be that there is no difference in size and the alternative hypothesis would be that the tomatoes are either bigger or smaller. If I then I picked 5 tomatoes out of each group and measured their diameter, I cannot be sure whether any difference in average size was caused by me accidentally picking bigger tomatoes in one sample compared to the other. Also the number of tomatoes I picked to measure would affect how accurate the measurement represents the true average of all the tomatoes I have grown. The P value calculated would represent the probability of me getting the same result by chance if there was no difference in the size of the t