Statistically Significant
A result is said to be significant or statistically significant if it is very unlikely to occur when the null hypothesis is true. That is, the result is sufficient to reject the null hypothesis. Thus, a treatment has a significant effect if the decision from the hypothesis test is to reject Ho.
When a hypothesis test is conducted using a computer program, the printout often includes not only a z-score value but also an exact value for p, the probability that the result occurred if the null hypothesis was true (that is, without any treatment effect).
For example, a research report might state that the treatment effect was significant, with z = 2.40, p = .0164.
When using exact values for p, however, you must still satisfy the traditional criterion for significance; specifically, the p value must be smaller than .05 to be considered statistically significant. Remember: the p value is the probability that the result would occur if were true (without any treatment effect), which is also the probability of a Type I error. It is essential that this probability be very small.