Recent comments in /f/dataisbeautiful

coffeesharkpie t1_j62z0bw wrote

I don't get your interpretation of the t-value and the 10% probability. To the best of my understanding the closer t is to 0, the more likely there isn't a significant difference between both samples. Now to get the p-value of the t-value we would need the number of dfs. But the p-values also don't tell us anything about the actual probabilities, but only how likely your data is, assuming a true null hypothesis (you'd need Bayesian statistics to get actualprobabilities).

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tinainthebar t1_j62y5fh wrote

That's an interesting claim, certainly believable if you look at direct deaths (which globally is probably under 100 - almost entirely from Chernobyl, especially if you count Kyshtym as military).

I'd love to see the source

Estimating, and attributing things like cancer correctly (reduction in life span and life quality) from things like construction and dismantling, uranium mining, etc is trickier.

On the other hand so is the mining for the metals needed for solar, and the construction risk per kWh I would guess are orders of magnitude higher for solar (especially rooftop solar)

I'm sure both are dwarfed by the impact from oil, gas and coal though.

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Optimal-Credit-1945 OP t1_j62wr8x wrote

It's more like 40% but I removed dependents so people living with parents. It will be lower than that still. But the chart is internally consistent and the point is that wherever the absolute levels lies it has fallen over two decades.

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Optimal-Credit-1945 OP t1_j62wmzk wrote

The data exists but it will look identical. There are 4 quarters of data a year so 80 datasets of 40-80k people all just to make a chart that would look the same. Also it would take so long for the transition to happen. anything less than a second per frame and you wouldn't be able to read what year it is. You would get really bored if this chart (remember it will look the same) took 20 seconds to transition.

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Optimal-Credit-1945 OP t1_j62wh9s wrote

You are both right. I removed people who were dependents of the head of the household. But most 15-19 yr olds are with parents many of whom have a mortgage. Here is a version of the chart with them included. I wanted to get to think more about people paying the bills. Very few 15-19 yr olds are not dependent - https://twitter.com/JonathanBoys/status/1596078094422769664

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zookeeper25 t1_j62qi7c wrote

People from different mother tongues marrying each other and their children speaking English at home is a fairly unique phenomenon from the last 10 years. 30 years ago those children were probably speaking Hindi at home.

Secondly, there is absolutely no correlation between those speaking English at home and those migrating to English-speaking countries. Almost everyone who has received a decent level of education has studied English in school. It’s not their mother tongue but it’s their second or third tongue - and that’s good enough to immigrate. Almost All university level education is in English. So the more educated people that you have encountered in your country have all studied a lot of their subjects in English

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