Final answer:
In experimental design, the population is the full set of individuals of interest, with the experimental units being the subjects when they are human. The explanatory variable is manipulated to measure its effect on the response variable. To ensure data reliability, treatments are randomly assigned, and methods like blinding and placebos are used to prevent bias.
Step-by-step explanation:
In a biological study, the population is the entire set of individuals of interest, while the sample is the subset of the population that is actually being studied. The experimental units are the individual members of the sample, and when these units are human beings, they are also referred to as subjects. The explanatory variable, also known as the independent variable, is the factor that the researcher manipulates and assumes will cause an effect on the response variable, which is the outcome being measured.
The study has two groups: the experimental group that receives the treatment, and the control group that does not receive the experimental manipulation. To reduce the influence of bias or the power of suggestion, blinding and placebos may be utilized. Blinding can involve keeping both the subjects and researchers unaware of which group the subjects have been assigned to, while placebos are fake treatments given to the control group that cannot influence the response variable.
Treatments are assigned randomly to eliminate the problem of lurking variables, ensuring that the only difference between the treatment groups is the exposure to the explanatory variable. This random assignment helps improve the reliability of the data collected and aids in drawing valid conclusions about the relationship between the treatment and the outcome.