Steve Tippins explains statistical significance: a decision rule that uses a probability threshold, usually a p-value of 0.05 or lower, to determine if research results are real enough to report. The p-value comes from probability theory and your sampling method, then gets compared against your chosen bar.
What really is statistical significance? Ultimately, we're looking to say, is there evidence to say that something that we're measuring is important at a level that we have said differentiates importance from not important? Statistical significance answers the question, do the results have an answer that I should talk about? Statistical significance is a bar, and if your answer is above or below, depending how you look at it, this bar it qualifies as significant. If it does not meet that level, or a p-value of 0.05, which is very common, 0.05 or lower, it's significant. If it's not at that level, or a higher number, it is not what is known as statistically significant. All of this depends upon probability and sampling to come up with this answer. Drop the word "help" in the comments, and I'll send you the link for my free dissertation help community.
