Is there a term for this type of unknown experimental interference?

In summary, the conversation discusses the importance of eliminating potential confounders in an experiment to confidently publish results. Specifically, the speaker mentions collecting 200 data points with two different inputs and getting output for each. However, they caution that just having a strong correlation between the input and output is not enough, as there could be other confounding variables at play. The speaker suggests using the term "confounders" to refer to these unknown alternate causes.
  • #1
.Scott
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TL;DR Summary
Term for unknown alternate causes in experiments.
You collect 200 data points, 100 with input ##A## and 100 with input ##A'##.
For all 100 ##A## you get output ##C## and for all 100 ##A'## you get ##C'##.
That's way more than 5 standard deviations, so you're ready to publish...

But not really.

Because what matters is not just that input ##A## is well-correlated to ##C## but that there is no ##B## that is also correlated to ##C##.
In the simplest (and probably worse) case, we may have collected all of the results from ##A## before any of the results from ##A'## - so there was a particular time when ##C## outputs ended and ##C'## outputs started. That would create many potential ##B##s: Room temperature or humidity were rising or falling; the experimenter was getting tired or more practiced; the apparatus broke or was wearing out.

So you are not ready to tout your 5 standard deviations until you run the experiment in a manner that reduces the likelihood that there could be such an unknown alternate cause. Is there a common (or otherwise better) term for such "unknown alternate causes"?
 
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  • #3
Dale said:
Maybe "confounders"
Yes, excellent! And I had run into that term before.
Thanks!
 

1. What is experimental interference?

Experimental interference refers to any external influence or factor that affects the outcome of an experiment, making it difficult to determine the true cause and effect relationship between variables.

2. What are some examples of experimental interference?

Examples of experimental interference include environmental factors such as temperature or lighting, experimenter bias, and participant behavior or performance.

3. Is there a term for this type of unknown experimental interference?

The term commonly used to describe unknown experimental interference is "confounding variable". This refers to any variable that is not being studied but still affects the outcome of an experiment.

4. How can experimental interference be controlled or minimized?

Experimental interference can be controlled or minimized through careful experimental design, randomization, and controlling for potential confounding variables. It is also important to replicate experiments to ensure that results are not due to interference.

5. What are the potential consequences of not addressing experimental interference?

If experimental interference is not addressed, it can lead to inaccurate or unreliable results, which can have serious consequences, especially in scientific research. It can also make it difficult to draw valid conclusions and replicate the experiment.

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