Factor vs Treatment
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.
Factor (in an experiment)
Collecting data and study design
A factor is an explanatory variable in an experiment whose categories, called levels, are imposed on the experimental units by the researcher.
You choose the factor and set its levels rather than just recording what happens naturally. For example, a baking experiment with one factor, oven temperature, might use three levels: 325, 350, and 375 degrees. When there is a single factor, the levels are the treatments. When there are two factors, the treatments are the combinations of levels, so pairing those three temperatures with two pan types gives 6 treatments.
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.