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I am a Geoscientist working in the field taking groundwater measurements every day. I frequently work with groundwater monitoring wells as an integral part of my day. For those of you who do not know what a monitoring well looks like, I have included a picture here.

Structure of a Monitoring Well
(source: water.ca.gov)

We use an electrical metal tape to take two measurements at each well. One for Depth to Water (DTW) and another for Total Depth (TD). This is measured in inches with decimals, eg. 4.56". These measurements are used for a wide variety of science such as potentiometric surface maps, groundwater flow direction and remediation strategies among other things.

Here is an example of a table of data that we create while gathering these measurements.

Well ID Depth To Water Total Depth
BH01 4.76 15.58
BH02 4.65 15.43
BH03 4.00 15.97
BH04 4.98 15.54
BH05 5.03 16.00

Each data set is from a site with a specific amount of wells, which can change according to the state regulations and presence of contamination. This is important because the data set for each site can grow or shrink over time. The well numbers can vary from 5 - 55 wells, each getting these two measurements every site visit. Other important information is the fact that one well can influence the measurement of another well, if water is added or drawn from a specific well, this can influence DTW at an adjacent well. Thus these wells are spatially related to one another.

Here is a fictional example that I created to illustrate what a typical site looks like.

Fictional Groundwater site

Which brings us to the question.

  • **How can I calculate the probability of getting a x.00" measurement? **

For context, for as long as I have worked at this company it has been coveted to get a DTW or TD measurement that ends in .00. It has led to many competitions, bragging rights, and debates amongst the engineers and scientists.

One school of though is that the measurement being taken is just out of 100, so x.00 happens 1/100 times. Thus the probability of getting a x.00 measurement is 1/100.

I however reject this idea, as I do not believe that the probability can be calculated that easily. For one thing there are multiple measurements per well, which increases your chances of getting an x.00. The Water levels change but typically the TD is fixed at a certain length (whatever it was drilled to). On top of that, I do no believe that these measurements come from a completely random sample, as stated above, one measurement can be related to the other both spatially and physically.

There is a plethora of data available for each site which I can use to calculate summary stats etc. My guess is that I would need to plot the current measurements in a frequency distribution and see if the measurements meet the normality assumption. If they do, then some of the common statistical tools I'm familiar with could be helpful. I keep getting stumped because I'm not interested in the continuous data, (ex. average DTW) I'm interested in a discrete event that occurs during measurement events and the frequency at which it occurs.

Any guidance on how to calculate this probability would settle years long office debates, and offer a new scientific tool to wield in the coveted chase to get a x.00. I am happy to provide more information or data as needed, and I am grateful to anyone who reads this post and has decided to answer.

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  • $\begingroup$ Studying the explanations of Benford's Law will take you far towards the answer you are looking for. The last method for generating uniform random variates I describe at stats.stackexchange.com/a/117711/919 also provides good insight: it shows how, for instance, the decimal part of a Normally distributed variable can be remarkably uniformly distributed provided only that the variable has a range spanning several "cycles" (of the integer parts of the data). Many other distributions will behave approximately the same. $\endgroup$
    – whuber
    Commented Aug 25, 2022 at 22:19
  • $\begingroup$ Another issue here is that the idea that there is an objectively true probability is highly problematic. For starters, given that data are not independent, you'd need to specify given what information you'd want a probability, because in order to make dependence play a role you'd need to model your probability as dependent on something specific in order to make it possible to compute it taking the dependence into account, and you may end up with different probabilities under different circumstances. $\endgroup$ Commented Mar 4, 2023 at 14:35
  • $\begingroup$ Another school of thought would say that probabilities are epistemic, meaning that they refer to a state of knowledge or even a subjective assessment (translating into potential betting rates) rather than to something that objectively exists in reality. Somebody may then well say that not specifying any particular reason why the probability should be specifically different there is no reason to choose the probability different from 1/100 (unless one wants to go for considerations regarding digit distributions in general settings as linked by @whuber). $\endgroup$ Commented Mar 4, 2023 at 14:41

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