# Paired t Test on Z normalized values

I have 2 sets of data, each consist of 92 data points. Pearson's correlation between them is 0.22. My hypothesis is the data sets are not significantly different, so I've normalized each datasets with Z score, and then did a paired t-test.

Here is the outcome post z score generation:

Pearson Correlation = 0.227190366262831
Observed Mean Difference = 7.61468183193993E-16
Variance of the Differences = 1.54561926747434
df = 91
t Stat = 5.87481796014581E-15
P (T<=t) one-tail = 0.5
t Critical one-tail = 1.66177115506169
P (T<=t) two-tail = 1
t Critical two-tail = 1.98637715441862

If I had used raw values then the outcome looks like this:

Pearson Correlation = 0.227190366262831
Observed Mean Difference = 18.2867152592913
Variance of the Differences = 239.53919514091
df = 91
t Stat = 11.3329069579844
P (T<=t) one-tail = 2.18898629577025E-19
t Critical one-tail = 1.66177115506169
P (T<=t) two-tail = 4.3779725915405E-19
t Critical two-tail = 1.98637715441862

What I can infer from this? Is this a correct approach to test these 2 datasets.