Final answer:
Based on the provided options and common statistical practices, Keisha likely used a t-test to analyze her data, assuming she compared the averages of two groups (e.g., control and test group) in a paired or matched sample scenario.
Step-by-step explanation:
To determine what statistical test Keisha likely used to analyze her data, we would need more context about the experiment. However, based on the options provided and considering a scenario where she compared two groups (a control group and a test group), if Keisha was analyzing the average difference in a certain metric between the two groups, she would likely use a t-test.
T-tests are commonly used when comparing the means of two groups to see if they are statistically different from each other. Given that one potential scenario could be that Keisha was examining the average decrease in tumor size, which is a comparison of means, options B (an f-test), and C (an r-test) would be less likely since f-tests are typically used to compare variances between groups and r-tests are not standard terminology for a common statistical test. Option D (Control Group) is not a statistical test at all – it's a part of experimental design.
Therefore, the t-test (Option A) would be a sensible choice to compare a single mean between the test and the control groups, assuming Keisha collected matched or paired samples. Examples of a t-test include a test of two independent means, a test of a single mean, or a test of matched pairs.