Always appreciate a stats refresher! I had both high school and college classes but don't use it in my daily life much so it's a ongoing battle against the constant atrophy of my knowledge base. Recently at work though, I've been voluntold into supporting a DEI-related* project and there's a lot of (software-assisted) regression analyses happening in the background. It definitely helps to have a solid grounding because then I can interpret the results too, not just rely on the vendor to explain.

*heavy on the E, hence the stats, and much less so on the D&I, happily

I always super appreciate your stats explainers. I really missed the boat on this stuff in school - my own fault - and this is just the right level of catch-up. You’re great at picking real-world examples that are easy to follow.

Thanks! This one got really low engagement and I'm not sure if that's 1) the topic isn't interesting (that's fine, this is a personal-interest blog) or 2) the explanation didn't make any sense (not fine, I pride myself on getting these things right). I thought it would help to show two very different, non-normal "games" and how they both average out to a normal distribution over a long number of plays. I'm aiming for the reader to thing "woah, that's normally distributed too!" on the second one, to really hammer home the idea that normal distributions come from the sampling procedure, rather than the sample.

I have to imagine the low engagement is more about the subject matter – I think it’s probably fairly rare for people to be in my boat, of being pretty undereducated about statistics, but not fully statistics-illiterate. I would guess you have more readers who don’t really need this explained as I did.

For what it’s worth, I thought your explanation of where the normal distribution comes from was easy to follow – I feel like I would be able to explain it to someone else in fairly simple terms now.

Always appreciate a stats refresher! I had both high school and college classes but don't use it in my daily life much so it's a ongoing battle against the constant atrophy of my knowledge base. Recently at work though, I've been voluntold into supporting a DEI-related* project and there's a lot of (software-assisted) regression analyses happening in the background. It definitely helps to have a solid grounding because then I can interpret the results too, not just rely on the vendor to explain.

*heavy on the E, hence the stats, and much less so on the D&I, happily

I always super appreciate your stats explainers. I really missed the boat on this stuff in school - my own fault - and this is just the right level of catch-up. You’re great at picking real-world examples that are easy to follow.

Thanks! This one got really low engagement and I'm not sure if that's 1) the topic isn't interesting (that's fine, this is a personal-interest blog) or 2) the explanation didn't make any sense (not fine, I pride myself on getting these things right). I thought it would help to show two very different, non-normal "games" and how they both average out to a normal distribution over a long number of plays. I'm aiming for the reader to thing "woah, that's normally distributed too!" on the second one, to really hammer home the idea that normal distributions come from the sampling procedure, rather than the sample.

I have to imagine the low engagement is more about the subject matter – I think it’s probably fairly rare for people to be in my boat, of being pretty undereducated about statistics, but not fully statistics-illiterate. I would guess you have more readers who don’t really need this explained as I did.

For what it’s worth, I thought your explanation of where the normal distribution comes from was easy to follow – I feel like I would be able to explain it to someone else in fairly simple terms now.