In order to conduct the t-test: Open a Google Sheet. Copy the mean heart rate data from your Table 2 into the sheet. You will use the formula =t.test, which in full looks like =t.test(range1, range2, tails, type). Begin typing in the formula and when you get to Range 1, highlight the first data set and then type a comma. Then highlight the next data set for your comparison (Range 2) and type a comma. Range 1 and Range 2 are the two data sets you want to compare (e.g. 0 min and 15 min). Next, for the tails, you want to type in '2', as we want to look both positive and negative changes. Then, for the type of t-test, you will type '1', as we want to use a paired t-test. Then hit Enter. So, the formula you enter in the cell on your sheet is: =t.test(*highlight data set 1*, *highlight data set 2*, 2, 1). After completing the t-test, a number will appear in that cell in the spreadsheet. This returned value is what is called a p-value. The p-value is the probability that the difference between the mean heart rates is due to chance and not due to the experimental variable, the chemical. If we receive a p-value of 0.24, this means there is a 24% chance that the experimental variable is not the cause of the change in mean heart rate (in the comparison of 0 minutes to 15 minutes, our experimental variable is exposure to the chemical for 15 minutes). We want to have 95% confidence in the results (or, less than a 5% chance that the chemical is not the cause of a change in mean heart rate), so we say that a p-value of less than 0.05 is statistically significant. The exact p-value that is the cutoff point for statistical significance can vary depending on the study, but often in biology research, a p-value of <0.05 is considered statistically significant. Then complete answer set attached. I will attach data for t-test.