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I had a colleague, Paula, studying jaguar (Panthera onca) who never got to see a jaguar in her entire three years in the field. Instead, the bulk of her research relied upon collecting and mapping jaguar droppings.

Fortunately for Paula, you can learn a lot from jaguar poo. Territories, diet, movements. She analysed the crap out of it.

Current reward systems combined with powerful cognitive biases - especially Confirmation Bias, Hindsight Bias, Observer Bias in conjunction with a strong Bias Blind Spot - favour progression-seeking behaviours over truth-seeking behaviours in scientific research and development.

Scientists are often quite intelligent.

This is a double-edged sword.

On the one hand, this allows them to rapidly adjust their world view based on their interpretation of new data.

On the other, it also means that they can quickly change their interpretation of new data based on their world view.

5. Exploring multidimensional spaces using low-dimensional tools may give rise to Hogarth spaces. These have the beguiling property of generating data to support scientists� initial intuitions no matter how flawed.

6. Scientists encountering a string of Hogarth spaces may soon develop a misplaced confidence, bordering on arrogance, in their scientific intuitions.

When researchers understand and control for sources of variability, it becomes easier for others to replicate the experiment and obtain similar results. Reproducibility and replicability are essential for confirming the validity of scientific findings.

But is this how it works in real life? Within the four walls of the laboratory, what do scientists really think about variability? More importantly, what do they do?