Data is getting weirder. Statistical models and techniques are more complex than they have ever been. No one understand what code does. But at the same time, statistical tools are being used by a wider range of people than at any time in the past. And they are not just using our well-trodden, classical tools. They are working at the bleeding edge of what is possible. With this in mind, this talk will look at how much we can trust our tools. Do we ever really compute the thing we think we do?
Can we ever be sure our code worked? Are there ways that it's not safe to use the output? While
"reproducibility" may be the watchword of the new scientific era, if we also want to ensure safety maybe all we have to lean on are pictures and fear.

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