I am trying to measure a statistically significant lift in sales and want to confirm appropriate methodology

Test Design

1. Created "Matched Markets" of 20 stores (10 in control vs. 10 in test)

Source Data (represented as total sales during test period):

Control Test

 100   185
 125   180
 135   170
 130   172
 140   190
 170   177
 165   165
 160   197
 162   185
 134   196

Methodology

I am running a one-tailed t-test since I do not know the SD of the population and we are hypothesizing that Test is greater than control. Based on this, I am calculating a p-value of .00003 with the result is significant at p < .05.

I want to confirm a t-test is appropriate here and I am not violating any assumptions around populations (since the stores in test vs. control are in different states) or anything else.

I am trying to measure a statistically significant lift in sales and want to confirm appropriate methodology

Test Design

1. Created "Matched Markets" of 20 stores (10 in control vs. 10 in test)

Source Data (represented as total sales during test period):

Control Test

 100   185
 125   180
 135   170
 130   172
 140   190
 170   177
 165   165
 160   197
 162   185
 134   196

Methodology

I am running a one-tailed t-test since I do not know the SD of the population and we are hypothesizing that Test is greater than control. Based on this, I am calculating a p-value of .00003 with the result is significant at p < .05.

I want to confirm a t-test is appropriate here and I am not violating any assumptions around populations (since the stores in test vs. control are in different states) or anything else.

I also wanted to confirm whether you are ALSO able to declare significance since the average of the test group (181.7) is greater than the Confidence Interval of control at 95% (calculated to be (142.1 ± 14)