I have a question/comment based on your first question You have 163 samples, which is quite large. We know that the t-distribution approaches normal for large n. Testing your H0 using the standard normal shown below indicates you shouldn't reject H0 i.e. means are not significantly different at 95%. Any response?

My thinking is that your data suggests a borderline case and you risk a Type I error. If the consequences are drastic you may want to rethink the conclusion.

One-Sample Z

Test of mu = 0 vs not = 0

The assumed standard deviation = 1.59

N Mean SE Mean 95% CI Z P

163 -0.240 0.125 (-0.484, 0.004) -1.93 0.054