How to pronounce “distributions” in English

distributions and to use it as a part of a longer term plan than to think of it as a reactionary quick cash in your

Distributions overlap, but men have a higher risk appetite.

Distributions overlap, but men have a higher-risk appetite or are less risk averse, if you want to put it that way.

- Normal distributions, the traditional explanation is that when there are a lot of effects that are random that are adding up,

and distributions of stars of different sizes masses to be what you'd expect and turn those into essentially the amount of light we'd expect in the optical and in the UV

but Pareto's income distributions were different.

And log normal distributions produce big inequalities.

And those distributions, unlike normal distributions where the central limit theorem says, they'll get more and more normal over time, they are unstable.

see great distributions, when everyone fails or everyone passes on some of your questions or tasks.

And what do their distributions look like in terms of the data?

Which provides distributions from the excess cash flow.

these probability distributions factorize.

And so we did distributions that way.

More or less even distributions like this right image are just far more likely, because there's far more ways to distribute your air molecules than

It requires me what are your probability distributions over?

It's more than just distributions.

Then we have to model these distributions, and then here is the most engineering, really.

And they appear in very patchy distributions in this lava tube because there isn't a whole lot for them to eat.

So I mentioned earlier we sometimes have distributions look like this.

I think that there are gender distributions, it's not that there's no differences among genders.

And if you look at the population distributions, there's a lot of overlap.

We tend to think random distributions look more like uniform distributions when random series tend to be clumpy and uneven, given the impression of pattern where

All hitters are streaky because random distributions are not uniform.

and given the absence of any distributions.

So we're drawing these distributions.

or inability to imagine overlapping distributions, to say that there can be a difference on average between males and females on whatever we're talking about.

When you move from the world of normal distributions to the world of power laws, things change dramatically.

- If you have events with one of these power distributions, what you're seeing most of the time is small events.

- We're used to living in this world of normal distributions and you act a certain way, but as soon as you switch to this realm

And then we also derive what kind of particle distributions can exist, can actually account for these radiation belts.

It looked virtually identical to the way that these distributions looked like within groups of children.

Here we're looking at three very asymmetrical distributions.

So you might be more familiar with probability distributions, where you say if you have, say, 16 different places that you might like to look for lunch, and you

while we collect the money and we do the loan distributions.

So the way we think of personality now is density distributions.

And then this generates a probability model of species distributions.

And the reason we don't have many probability distributions that look like this but rather that look like this is because a range of things can happen.

It's a right hand draw from both of those distributions.

I've been depicting them with these normal distributions, but of course, that's not the case.

So we're going to sample from these distributions and then run an analysis for each one of them.

But the first large task and the first large distributions were in...

The system tends to gravitate to those long tailed distributions, and you might wonder why.

And well, using these distributions, you can compute an average from 0 to 1, and we have that here on these magnificent Google Maps.

So there's a big overlap in the distributions of height between men and women.

There's this concept called the 1/f noise and 1/x distributions where often, you know,

And the key caveat of why quantum is different from these types of probability distributions is that classically, we know how to sample

and for gay couples, because the hormone distributions are very, very different.

And on a constant valuation, absent any distributions, that's sort of my very modest level of a proof of this notion.

can tell that by the the unequal distribution of our schools the unequal distributions of mass transit the