Final answer:
Courtney's data indicating that her times are always faster after consuming high carbohydrate meals or lunch in general would likely prompt her to revise her study. Scientific methodology demands changes in the experimental design when data contradict initial hypotheses, such as in a controlled experiment.
Step-by-step explanation:
The evidence in Courtney’s data that would most likely lead her to change the way she is conducting her study is if she noticed overall, her high carbohydrate meals gave her faster times (Option C). This observation suggests that the type of meal consumed may have a direct effect on her performance, thereby challenging her initial hypothesis or the current methodology of the study. If her times were always faster after eating lunch, regardless of the meal type (Option D), it could indicate that the time of day rather than the meal content is the critical variable.
When one’s own data contradicts the initial hypothesis, a scientific approach would demand a revision of the experimental design. For example, in a controlled experiment testing if breakfast consumption affects attention in class, the observer may hypothesize that attention is better after consuming breakfast. However, if the data collected shows consistent increases in work times after having breakfast, as seen in a scenario where a p-value of 0.0004 is less than the alpha of 0.05, the null hypothesis would be rejected. This decision suggests that breakfast indeed has a significant impact on work times.