Hello,

I need to analyze an experiment... could you help me?

Stewart Fist reported the results of an experiment investigating the link between cell phone use and tumors in mice. the study exposed 100 mice to cell phone radiation for 2 1/2 hour periods each day for 18 months. The researchers fitted another 100 mice with the same type of antennas, which never had the power turned on. The tumor rate was twice as high in the exposed group vs. the unexposed group.

I know the question, population and sample, but I am having trouble identifying potential bias or finding lurking variables. This experiment looks pretty clean to me.

Thank you,

Scarlett

Hello Scarlett,

I can assist you with analyzing the experiment and identifying potential biases or lurking variables.

First, let's define the terms.

- Potential bias refers to any factor that may cause the results of the study to deviate from the true population value. It can lead to the overestimation or underestimation of the relationship between the variables being studied.

- Lurking variables are unobserved variables that may affect the relationship between the variables of interest. They can introduce bias and lead to incorrect conclusions.

Now, let's analyze the experiment together.

1. Population and Sample:
- The population in this case would typically be mice, as they are the subjects under study.
- The sample consists of the 200 mice involved in the experiment.
- It is important to note that the results of this study can only be generalized to mice and not directly extrapolated to humans.

2. Potential Bias:
- One potential bias could be selection bias. The researchers may have selected specific mice for the exposed and unexposed groups based on certain characteristics, which could introduce bias and affect the results.
- Another potential bias could be observer bias. If the researchers knew which mice were in the exposed and unexposed groups, they might unintentionally influence the outcome through their observations or data collection methods.

3. Lurking Variables:
- One lurking variable in this experiment could be genetic variability among the mice. If there are genetic differences between the mice in the exposed and unexposed groups, these differences could affect the tumor rates independently of cell phone radiation.
- Another lurking variable to consider is the overall health of the mice. If there are pre-existing health conditions in either group of mice, it could affect tumor rates independently of cell phone radiation exposure.

To address these potential biases and lurking variables, researchers typically employ randomization techniques, blinding, and control groups. Randomization helps ensure that the mice chosen for each group are representative of the population. Blinding prevents researchers from knowing which mice are in which group to avoid observer bias. A control group, which in this case are the mice fitted with antennas but not exposed to radiation, helps isolate the effect of the cell phone radiation.

In conclusion, while this experiment appears to be designed reasonably well, it is essential to be aware of potential biases, such as selection bias and observer bias, and consider lurking variables, such as genetic variation and overall health of the mice. Addressing these concerns through randomization, blinding, and control groups can help mitigate bias and provide more reliable results.

I hope this clarifies the potential biases and lurking variables in the experiment. If you have any further questions or need more assistance, feel free to ask!

As far as the experiment goes, it also "looks pretty clean to me." However...

If you want to generalize this data to humans, do humans use cell phones that often/long? (I know I don't.) Also, would the increase in body mass of humans effect the result?