What's Going on in Ohio?

In early March, something unusual happened in Northeast Ohio.

Not a single Bigfoot sighting, but a cluster of them.

Over the course of a few days, multiple independent witnesses across Portage County reported encounters with something large, upright, and undeniably not human.

Some described figures between 6 feet and 10 feet tall, moving through wooded areas, crossing roads, and even appearing near homes.

Others reported hearing grunts, movement in the tree lines, and animals reacting in fear, including one dog that was said to be visibly shaken after an encounter.

Unfortunately, there were no photos or videos, but the stories were all relatively similar.

As many of you may know, I used to be involved in statistical research and analysis as part of my job as a safety professional. We like to kid that there are "lies, damned lies and statistics," partially because the numbers are often used to tell a story, and while the numbers don't lie, the interpretations can vary.

We are wired to find patterns—even when they aren't there. This tendency is known as apophenia. It's why we see faces in clouds, connect unrelated events, and turn coincidences into narrative.

So, when multiple people in the same region report something unusual, it can create a feedback loop:

1. One sighting is reported

2. Awareness increases

3. More people interpret ambiguous experiences into something familiar—I mean what else could explain what you just saw? Right?

4. Reports increase.

The clusters become self-reinforcing.

Clusters happen, even when nothing is happening. One of the most important ideas in statistics is that random events don't spread out evenly. They clump.

This is often called Poisson distribution behavior—a model used for things like:

• Earthquakes

• Disease outbreaks

• UFO sightings

• And yes, Bigfoot reports

Even if sightings were completely random, you'd expect periods of nothing, followed by sudden bursts. To human observers, these bursts might feel significate. To a statistician, it might be completely expected.

But not all clusters are meaningless. And here's where it gets interesting. Statisticians don't dismiss clusters outright—we test them.

We ask:

• Is the frequency higher than expected?

• Is there a geographical pattern beyond randomness?

• Does it repeat over time?

If the answer is yes, then you may be looking at a real underlying cause. These same statistical questions are used to identify:

• Environmental hazards

• Crime hotspots

• Disease outbreaks

  
  

So, the question becomes, does the Ohio cluster exceed what randomness would predict? Right now, there's no evidence that it does. But remember what Lauren says in The Veritas Codex, "Absence of evidence is not evidence of absence." and "We need more data!"

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