Those who know me know I’m a ‘Stat’. Sounds boring I know! My UCL Honours degree is in Economics and Statistics. I particularly loved ‘Statistical Inference’ – what you can and can’t conclude from a set of data. It often proves vital in my coaching, enabling clients (decision-makers) to reveal hidden flaws in their thinking, avoid making inaccurate conclusions from ideas or sets of data, and hence make sound management decisions.
It applies in relational worlds as much as technical ones. Sometimes it saves a fortune in social or financial terms!
We often see cherry-picking of data to ‘prove’ a point rather than testing whether it holds up or not. Then bad decisions are made, or people reject the decision when they see it is unfounded, even when there is a good sentiment behind the idea.
Even the ‘big guns’ can engage in it. Here’s an example I just wrote about McKinsey’s (not good) use of statistics in this way.
PS just because I critique a statistic or a policy based on poor statistics doesn’t mean I support the opposite view. That’s poor statistical inference too! It’s about getting it right and fair.
Let’s do better with Stats! DM me if you see stats being abused or want to check your own conclusions (inferences)
hashtag#statspolice!