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### Course: High school statistics>Unit 5

Lesson 4: Introduction to experimental design

# The language of experiments

Karina wants to determine if kale consumption has an effect on blood pressure. She recruits $100$ households and randomly assigns each household to either a kale-free diet plan or a kale-based diet. At the end of two months, she plans to record the original and final blood pressures for members of each household.
Problem 1
What is the explanatory variable?

problem 2
What is the response variable?

Problem 3
What are the treatments?

problem 4
Who or what are the experimental units?

## Want to join the conversation?

• Why wouldn't the answer for problem 4 be the members of each household?
• The members of each household receive the same diet, but each household could have a different diet. Since the diet is consistent in the household, the household is the experimental unit.
• Words are slippery. The last question expects as correct answer the households, not their members. Makes me scratch my head and and ironically conclude: "Aha! So it is the households who eat (or not) the kale, not the household members".
• That is a funny point, but the household is the whole of the household members. We were comparing different households as a whole and not a households individual members.

Hope this helps,
- Convenient Colleague
• why didnt seattle just run the ball..
• It was the right call but Malcolm Butler just made a great play.
• If the household members are not the experimental units, then what are they?
• If the household members are not considered the experimental units, then they are the subjects or participants of the experiment. In this study, the household members are the individuals whose blood pressure measurements are being recorded before and after the two-month period. Therefore, they are the subjects or participants of the study.
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• What can be the possible source of bias here ?
• Possible sources of bias in the study could include:

Selection bias: if households are not randomly selected or assigned to treatment groups.
Measurement bias: if blood pressure measurements are inaccurate or inconsistent.
Non-response bias: if participants drop out or refuse to participate.
Reporting bias: if participants do not accurately report their adherence to the diet plan.
Observer bias: if individuals recording blood pressure are aware of the assigned treatment group and this influences their measurements.
• this was very easy