The t-test is a statistical test used to determine if there is significant statistical evidence for a difference in means between two groups.
Essentially, what this means is that it's used to figure out whether or not two groups have different means. When we run a t-test, it returns to us a t-score and a P-value. P-value is derived from the t-score, and this P-value is essentially the probability that the null hypothesis would produce the observed results displayed in the question. In order to determine if we should reject or fail to reject our null hypothesis, the P-value determined by the t-test should be lower than the significance level. If the question doesn't prompt for a specific significance level (which is usually displayed symbolically as α), then we can generally use 0.05 as the significance level.
I'll admit, this whole concept is pretty confusing. Statistics is a surprisingly hard class. If you have any questions about anything I wrote here or would like me to explain any concept I mentioned further, don't be afraid to ask me!
- breezy ツ
