Final answer:
The independent variable is shaving legs, and the dependent variable is sprinting speed in a study hypothesizing that shaving legs improves sprinters' speed. Reliability in the experiment is key, ensuring results can be replicated under consistent conditions and isolating the cause-and-effect relationship.
Step-by-step explanation:
In the scenario presented, the independent variable is the act of shaving legs, and the dependent variable is sprinting speed. The hypothesis suggests that shaving legs will make sprinters run faster. This hypothesis implies a causal relationship, where the change in the independent variable (shaving legs) is expected to result in a change in the dependent variable (sprinting speed).
When designing an experiment, it's crucial to ensure the study's reliability. Reliability refers to the likelihood that the observed effects can be replicated under consistent conditions. For instance, as in cooking, using a measuring cup ensures that the recipe produces the same results each time, indicating high reliability. Similarly, in experiments, accurate tools and methods are implemented to ensure that the changes observed in the dependent variable are attributable to the manipulation of the independent variable.
As such, if a study was conducted with a group of sprinters, some who shaved their legs and some who did not, the researchers would need to control for other variables that could affect sprinting speed. The objective is to isolate the effect of the independent variable on the dependent variable. Accurate measurements and standardized conditions would be vital to ensure the experiment's reliability and validity.