Blinding vs Double-Blind
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.
Blinding
Collecting data and study design
Blinding keeps people in an experiment from knowing which treatment a subject received, so their expectations cannot bias the response or its measurement.
Blinding prevents knowledge of the treatment from coloring how subjects respond or how researchers measure outcomes. In a single-blind study the subjects do not know their group; blinding the people who assess results guards against biased scoring. For example, a taster who does not know which cola is brand A rates the flavor on taste alone. Without blinding, expectations can nudge both the response and its measurement toward what people hope to see.
Double-blind
Collecting data and study design
A double-blind experiment hides the treatment assignment from both the subjects and the people who interact with them or measure the response.
A double-blind design blocks bias from two directions at once: neither the subject nor the researcher measuring the outcome knows who got which treatment. That stops a subject's expectations and a researcher's hopes from shaping or scoring the response. For example, in a vaccine trial neither the volunteer nor the nurse recording symptoms knows if a shot was vaccine or saline, while a separate code tracks it. It is the standard for clinical trials because it removes the strongest sources of response and measurement bias.