In principle, a statistically significant result (usually a difference) is a result that's not attributed to chance. More technically, it means that if the Null Hypothesis is true (which means there really is no difference), there's a low probability of getting a result that large or larger.Oct 21, 2014
If the computed t-score equals or exceeds the value of t indicated in the table, then the researcher can conclude that there is a statistically significant probability that the relationship between the two variables exists and is not due to chance, and reject the null hypothesis.
Statistical significance means that the result observed in a sample is unusual when the null hypothesis is assumed to be true. When testing a hypothesis using the P-value Approach, if the P-value is large, reject the null hypothesis.
So if your sample size is big enough you can say that a t value is significant if the absolute t value is higher or equal to 1.96, meaning |t|≥1.96.Dec 11, 2016