Control Groups, Placebos & Blind Experiments (College Board AP® Statistics)

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Mark Curtis

Written by: Mark Curtis

Reviewed by: Dan Finlay

Control groups & placebos

What is a control group?

  • A control group is a treatment group in an experiment that are purposefully given either

    • an inactive form of the treatment

    • or the pre-existing (baseline) treatment

  • Having a control group makes it easier to determine whether the treatment of interest (applied to another group) has any effect

Examiner Tips and Tricks

It is not correct in the exam to say that a control group receive 'no treatment', because being in a control group is, in itself, a type of treatment!

What is a placebo?

  • A placebo is a dummy (inactive) treatment that the experimental units believe is an active treatment

    • e.g. telling individuals they are taking a pain-relief drink when in fact it is water

  • Control groups can use placebos as inactive forms of treatment

    • though placebos are not always required

      • e.g. when comparing a well-established old treatment to a new and untested treatment

What is the placebo effect?

  • In some cases, experimental units may show a response to a placebo

    • This type of response is called the placebo effect

      • e.g. feeing like you are smarter after taking what you thought was an intelligence pill (which turned out to be just a sugar pill)

Single & double-blind experiments

What is a single-blind experiment?

  • A single-blind experiment is one in which the participants do not know which treatment they are receiving

    • e.g. participants do not know if they have a placebo pill or a real pill

      • It helps to reduce the placebo effect

      • as it stops participants changing their behavior based on knowing what treatment they are having

  • The researchers conducting the experiment know which participants received which treatments

What is a double-blind experiment?

  • A double-blind experiment is one in which participants and the researchers (in particular those interacting with participants and measuring their responses) do not know which groups are assigned which treatments

    • This helps to reduce the placebo effect

    • and also helps to reduce any bias introduced by the researchers themselves (consciously or unconsciously)

  • There will be an experimental designer (who is not a participant, nor a researcher measuring the responses of the participants) who will know which participants received which treatments

    • After the experiment has been conducted, the results are revealed

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Mark Curtis

Author: Mark Curtis

Expertise: Maths

Mark graduated twice from the University of Oxford: once in 2009 with a First in Mathematics, then again in 2013 with a PhD (DPhil) in Mathematics. He has had nine successful years as a secondary school teacher, specialising in A-Level Further Maths and running extension classes for Oxbridge Maths applicants. Alongside his teaching, he has written five internal textbooks, introduced new spiralling school curriculums and trained other Maths teachers through outreach programmes.

Dan Finlay

Author: Dan Finlay

Expertise: Maths Lead

Dan graduated from the University of Oxford with a First class degree in mathematics. As well as teaching maths for over 8 years, Dan has marked a range of exams for Edexcel, tutored students and taught A Level Accounting. Dan has a keen interest in statistics and probability and their real-life applications.