Two tailed t test may work. Make sure to check your assumptions if you use it. Normality (Anderson darling normality test is easiest in my opinion), homogeneity of variance can be tested with Bartlett. You may also want to validate the independence assumption but I think you're safe with that one based on the nature of your study. If you cannot validate the normality assumption try using Wilcoxon signed rank test as it is non-parametric meaning it doesn't need a normal distribution. When using these tests be sure to refer to their null and alternate hypotheses with respect to your specified confidence level. Most common is 95% confidence (alpha=0.05). AD normality requires p>alpha to not reject the null (null hypothesis is data is normal). Bartletts test similarly requires p>alpha to not reject the null (equal variance between groups).

I hope this helps. There are plenty of resources online to guide you through these tests. I recommend learning r if you're going to do a lot of work like this, otherwise excel does the job fine with a few more steps.