Treatment vs Experiment
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Treatment
Collecting data and study design
A treatment is a specific condition applied to subjects in an experiment, whose effect on a response variable the experiment is designed to measure.
A treatment is what the experimenter imposes on each group so their responses can be compared. For example, in a study of a new fertilizer, one treatment might be the new fertilizer and another the current fertilizer, with plant growth as the response. When an experiment varies more than one factor, each treatment is a combination of the levels of those factors. Subjects are assigned to treatments at random so the groups start out comparable.
Experiment
Collecting data and study design
An experiment imposes treatments on subjects and compares their responses, supporting a cause-and-effect conclusion when treatments are assigned at random.
In an experiment the researcher actively assigns treatments rather than just observing what happens. For example, randomly assigning patients to take a new drug or a placebo and then comparing recovery rates is an experiment. Random assignment balances out other variables across the groups, which is what lets a difference in response be attributed to the treatment. Its key ideas are comparison, random assignment, and replication across many subjects.