How wide was the Equifax data breach?

143 million US consumers were caught up in the data breach. I keep seeing it portrayed as 44% of the US population. But, the US population includes children. Initially, it seemed to me the better metric was 11 million more than all of 2016 IRS tax filers. The problems with this latter comparison? Lots of… Continue reading How wide was the Equifax data breach?

Better Predictions

13.7: Cosmos and Culture has a good article on predictions. Making good predictions isn’t just about your accuracy; it’s also about your calibration. Accuracy = how often correct Calibration = confidence level in the prediction All too often when we see predictions no one asks about the calibration. Nor do we go back and check the… Continue reading Better Predictions

Solution to Black-On-Black Crime

(This post on black-on-black crime is satire. Thought I would point that out before someone gets too upset over it.) A Georgia state lawmakers showed concern about the amount of black-on-black crime. He is obviously referencing the FBI homicide statistics for perpetrator race. Fortunately the actual number is lower than the 98% he claimed. But he’s not… Continue reading Solution to Black-On-Black Crime

Review: Dataclysm: Who We Are

Dataclysm: Who We Are by Christian Rudder My rating: 3 of 5 stars Maybe really 2.5 stars, but I rounded up. I have read the OkTrends blog since its inception. Human behavior fascinates me, so I take any opportunity to read on it. The We Experiment On Human Beings post ensnared my attention since it… Continue reading Review: Dataclysm: Who We Are

Shortcuts: Math

(This post is part of a series. Intro > 1. Illusions > 2. Labeling > 3. Math > 4. Multitasking) Behavioral economics fascinates me. Humans have amazing abilities to miscalculate risk with extreme confidence they accurately assessed it. These appear to be rules of thumb which work in certain situations, but really are not applicable to others yet most people do. Part of the… Continue reading Shortcuts: Math

Accounting Predictions

In my Prediction Accountability, I ranted on how no one really knows whether predictions are accurate and ended with it really does not matter because no one is going to really stop using these services because they are usually wrong. Basically, I thought it futile to even try. In retrospect that is probably the perfect… Continue reading Accounting Predictions

Prediction Accountability

The technology buzzword standard for prediction appears to be Netflix and Amazon. Everyone wants to get to where they make recommendations customers will buy. But are these predictions any good? Out of the slew of emails you get from Amazon, how percentage do you actually buy? How many do you sneer at it and hit… Continue reading Prediction Accountability