Final answer:
Neither text messages sent nor phone calls made can be definitively classified as explanatory or response variables without further context on the study's intent. The closly correct option is a) and b).
Step-by-step explanation:
In a dataset of the number of text messages sent and phone calls made by 100 students, one is typically considered the explanatory variable and the other the response variable. The explanatory variable is the one that is believed to cause, or explain, changes in the response variable. In this context, however, there is no clear causal relationship between the two variables, as the number of text messages a student sends does not necessarily cause a change in the number of phone calls they make, and vice versa. Therefore, neither a) nor b) is definitively correct without more context on the intent of the study. Both variables could influence each other, or they could be independent. Hence, both c) and d) are incorrect as well because, in a typical study, you would not have both variables as explanatory or both as response variables. Usually, you would have a hypothesis about how one variable might predict or affect the other to assign them accordingly.
When considering the research terms mentioned, the population would generally be the larger group from which the sample is taken, in this case, college students. The sample refers explicitly to the 100 college students included in the study. Experimental units are the individual members of the sample; in this case, each student. The term treatment refers to the different conditions to which the experimental units are subjected. In a hypothetical scenario where the size of tableware is manipulated to see its effect on food intake, 'the size of the tableware' would be the explanatory variable, whereas 'the amount of food eaten' is the response variable, and the smaller tableware would be considered the treatment.