Control, Placebo, and Blinding
A free Statistics and Data Analysis lesson from the “Collecting Data” unit, with a worked example and practice problems including step-by-step solutions.
Good experiments reduce avoidable bias. Control groups provide a comparison, placebos separate treatment effects from expectation effects, and blinding reduces the influence of what people know about the treatment. This lesson builds the habit of reading the context first, choosing the right statistical tool, calculating carefully, and then writing what the result means. By the end, students should be able to do the computation and explain why that computation answers the question.
What you'll learn
- Explain the role of a control group
- Identify placebo effects
- Explain single and double blinding
Worked example
Problem. A medicine study gives one group a pill with no active ingredient that looks like the real pill. What is that pill called?
- Worked Example: First identify exactly what the question is asking: A medicine study gives one group a pill with no active ingredient that looks like the real pill. What is that pill called?
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- A placebo looks like a treatment but lacks the active ingredient.
- It helps separate treatment effects from expectation effects.
Answer: placebo
Practice problems
1. Practice case A: What is the purpose of a comparison group in an experiment?
Choices: to provide a baseline for comparison · to choose the sample randomly · to make a survey question neutral · to compute a histogram
Show solution
- Warm-up: First identify exactly what the question is asking: What is the purpose of a comparison group in an experiment?
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- A control group shows what happens without the new treatment.
- That makes the treatment effect easier to judge.
- Verify the selected choice by checking that it satisfies the original prompt and that the other choices fail the same test.
Answer: to provide a baseline for comparison
2. Practice case B: A no-active-effect version of a treatment is a:
Choices: parameter · cluster sample · standard error · placebo
Show solution
- Warm-up: First identify exactly what the question is asking: A no-active-effect version of a treatment is a:
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- A placebo mimics the treatment experience.
- It helps account for expectations.
- Verify the selected choice by checking that it satisfies the original prompt and that the other choices fail the same test.
Answer: placebo
3. Practice case C: Participants do not know which treatment they receive, but researchers do. What is this?
Choices: voluntary response · cluster sampling · single blinding · double blinding
Show solution
- Warm-up: First identify exactly what the question is asking: Participants do not know which treatment they receive, but researchers do. What is this?
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- Single blinding hides treatment information from participants.
- Researchers still know the assignments.
- Verify the selected choice by checking that it satisfies the original prompt and that the other choices fail the same test.
Answer: single blinding
4. Practice case D: Neither students nor graders know which review plan each student used. What is this?
Choices: undercoverage · double blinding · single blinding · simple random sampling
Show solution
- Warm-up: First identify exactly what the question is asking: Neither students nor graders know which review plan each student used. What is this?
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- Double blinding hides assignments from participants and evaluators.
- That reduces expectation and measurement bias.
- Verify the selected choice by checking that it satisfies the original prompt and that the other choices fail the same test.
Answer: double blinding
5. Practice case E: Why should outcome evaluators sometimes be blinded?
Choices: bias from knowing the treatment · sample size · all random variation · the need for any data
Show solution
- Warm-up: First identify exactly what the question is asking: Why should outcome evaluators sometimes be blinded?
- Compare each answer choice with the calculation or rule, and eliminate choices that do not satisfy the condition.
- Knowing the treatment can change behavior or judgment.
- Blinding reduces that influence.
- Verify the selected choice by checking that it satisfies the original prompt and that the other choices fail the same test.
Answer: bias from knowing the treatment
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