as in writing: brevity is the soul of wit.

This seems very unnecessarily busy. There's absolutely no reason for the ranking to be a giant doughnut graphic scaled to the size of the thing that's already shown by the choropleth map underneath.

The rankings, which probably aren't needed at all, could just be added in the label for the state (e.g., 22.862 (1) for PA) or just put in a separate table.

Ah, starting change over time figures from weird baselines. Always so much fun.

I did a community emergency response training with a retired firefighter in the cook county suburbs.

He told us about when he was dealing with something involving effluent into a waterway and the director of the water reclamation district (who he had not met) showed up and started giving orders he asked one of his colleagues who she was and they just said, "she's god. You do what she says."

The city's water district is atypically powerful and just kind of weird in general.

Utilities in the US are generally considered natural monopolies. That is, it's unreasonable for a competitor to build duplicate infrastructure to compete. The costs are too high. Only one firm can really provide the service to a market.

As such, they're highly regulated. Prices, staffing, availability, quality, etc. are all highly prescribed by the local or state government.

So why not make them government owned? Well, it's a trade off. Public utilities tend to be less innovative and have less of an incentive to invest in improvements. Private ones have less of an incentive to provide stable, low prices and service.

But what if I want to pay $30 for a crappy sandwich in the terminal?

Card balances means that the issuer is paying merchants but not getting paid back by the card holder. It also implies a higher risk of default. You don't make money on interest until you start getting paid back.

I mean, card interest rates should loosely track balances. If more people are holding a balance that means the issuer needs higher rates to maintain the same revenue. Obviously the latest increase has much more to do with interest rate increases, but the fact that these two are tightly intertwined is very unsurprising.

My dude, you're basically looking at women as vending machines for sex.

"How to not be a creep: Continue to look at women as sex objects, but look at them as complicated sex objects."

> Soo…. The majority of women are overweight?

Yes. A smaller percentage, around 40%, are obese according to BMI.

People labelled as obese and underweight according to BMI tend to be at much higher risk for various health problems. The evidence is less concrete for the overweight, but not obese group. The reason is basically exactly what you're getting at. You can be overweight by being particularly muscular, etc.

BMI is an incredibly rough measure of your physical condition. At the extremes (obese and underweight) it is definitely associated with health problems. At more middling levels the fuzziness and imprecision of the measurement makes it less useful as a gauge for health risks.

These arguments tend to forget the fact that people don't tend to buy ineffective products.

It started with the corn chips with the mild salsa. Then I kept going hotter and hotter. I couldn't stop myself. Only intesnsive outpatient guac therapy was able to break the cycle.

The laptop underpowers its components when not plugged in to conserve battery life. That's really the long and short of it.

Categorical data are data that track a characteristic in which people are put into non-quantifiable, mutually-exclusive categories.

If I want to measure if you're from New York, you either are or you aren't. You can't be 0.7 New Yorks. Everyone exists in one of two categories, from New York and not from New York.

We can split categorical data into two subtypes, ordinal (order matters) and nominal (order doesn't matter). The "from New York/not from New York" is an example of nominal data. If I wanted to put people into categories based on their income (e.g., $0-$10000, $10001-$20000, etc.) it would be ordinal. The information being tracked is still not quantitative (we're just tracking your membership in a category), but there is an order to the categories.

The terms "polynomial" and "binomial" do not make sense to use in the context of categorical data. It sounds like you may just be using them to refer to nominal data that track 2 categories vs. more than 2 categories. The former is often referred to as a "binary variable" because it has two states (e.g., "In New York" and "Not in New York").

Could you provide some context? I don't think your question provides enough information to give you a meaningful answer.

I mean, the first step is to find a career.

The first step to doing that is to figure out what you might like. The best way to do this is to talk to people who work in roles you think sound interesting. You would be surprised how many people are willing to take a half hour to talk with you about their job if you just cold email them. That said, people you know are much more likely to say yes.

A lot of these conversations will also come with various recommendations for you to pursue and may even directly lead to a job opportunity. This kind of networking is the key to finding a good job.

I mean, a nation state tried very hard to commit out and out genocide against Jews 80 years ago...