"Designing an Experiment Researchers want to know if there is a link between hypertension (high blood pressure) and consumption of salt. Past studies have indicated that the consumption of fruits and vegetables offsets the negative impact of salt consumption. It is also known that there is quite a bit of person-to-person variability in the ability of the body to process and eliminate salt. However, no method exists for identifying individuals who have a higher ability to process salt. The U.S. Department of Agriculture recommends that daily intake of salt should not exceed 2400 milligrams (mg). The researchers want to keep the design simple, so they choose to conduct their study using a completely randomized design.


For each factor identified, determine whether the variable can be controlled or cannot be controlled. If a factor cannot be controlled, what should be done to reduce variability in the response variable?"

Verified step by step guidance

1. Identify the factors mentioned in the problem: (1) salt consumption, (2) consumption of fruits and vegetables, and (3) person-to-person variability in salt processing ability.
2. Determine which factors can be controlled: Salt consumption can be controlled by setting specific intake levels (e.g., below or above 2400 mg), and consumption of fruits and vegetables can also be controlled by assigning specific diets to participants.
3. Recognize that person-to-person variability in salt processing ability cannot be controlled because there is no method to identify individuals with higher or lower ability.
4. To reduce variability from the uncontrollable factor (person-to-person variability), use randomization in the experimental design. This helps distribute the variability evenly across treatment groups, minimizing its impact on the results.
5. Additionally, consider increasing the sample size to further reduce the effect of variability and improve the reliability of the conclusions.

Key Concepts

Factors and Variables in Experimental Design

Factors are the independent variables that researchers manipulate or observe to study their effect on the response variable. Variables can be controlled (set or fixed by the experimenter) or uncontrolled (cannot be fixed or manipulated). Identifying which factors can be controlled helps in designing the experiment to isolate effects and reduce confounding.

Completely Randomized Design

A completely randomized design assigns experimental units to treatments entirely at random, ensuring each unit has an equal chance of receiving any treatment. This design helps to evenly distribute uncontrolled variability across treatment groups, minimizing bias and allowing for valid statistical inference.

Reducing Variability from Uncontrolled Factors

When factors cannot be controlled, researchers use techniques like randomization, blocking, or increasing sample size to reduce variability in the response variable. These methods help to balance or account for the uncontrolled variability, improving the reliability and validity of the experiment’s conclusions.