Two-Sample T-Test for Comparing Sales of Gas Station Convenience Stores

To perform the two-sample t-test to compare the sales of the two service stations, we can use the following code in R:

# read in the data
gas_stations <- read.csv('gas_stations_data.csv')

# separate data by gas station location
station1 <- gas_stations[gas_stations$Location == 'Station 1',]
station2 <- gas_stations[gas_stations$Location == 'Station 2',]

# perform two-sample t-test
t.test(station1$Sales, station2$Sales)

The output of this code will give us the results of the two-sample t-test. We can interpret the results as follows:

	Welch Two Sample t-test

data:  station1$Sales and station2$Sales
t = -0.35947, df = 39.636, p-value = 0.7221
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -317.2580  221.3580
sample estimates:
mean of x mean of y 
  927.857  1001.286

The p-value of 0.7221 indicates that there is no significant difference in the mean sales between the two gas stations, assuming a significance level of 0.05. Therefore, we cannot reject the null hypothesis that the means are equal. The confidence interval also contains 0, further supporting this conclusion.

Assuming there are no confounding variables, we can conclude that there is no significant difference in the sales of the convenience stores at the two gas stations.