How to pronounce“regressions”in English

regressions and logistic regressions we did a lot of that then we did some research on how to redo our analyses

regressions with the log of that or with that interactive with something else.

regressions that you would find a u-shape or not of course you know i think controlling for these variables could

regressions before you know that i can still find patents on in this data even though i don't know i don't know what the features mean and

quantile regressions rather than ols because prior research indicates that monitoring is effective in the tails of

polynomial regressions so squared terms negative for cap x inverse u shape spline regression

I ran my regressions past him just to make sure I had done it right and he said, "Yeah, it all looks good and damn I wish my regressions looked like that, too."

You may not have regressions but that doesn’t mean you’re going to improve student engagement or help kids catch up.

And then run regressions for reporting status here this is reporting financial for firm i in time t.

So when we run regressions, you're going to test the hypothesis about whether the coefficient is zero.

knowing that was uip regressions didn't give us much well i think the way to see something is to realize that uip

Running those regressions gave me clarity.

Do whatever regressions we can to find good correlations that are worth digging into and then we dig further into those.

These guys did a whole bunch of regressions.

And they have a lot of other regressions in their paper.

We did 108 different tests and regressions on quality at the individual question level.

So we're in the regressions setting here, and how is the regression tree going to pick splits for this task?

So you can run these regressions within firm, there's nothing keeping you from doing that.

you can do some simple or less regressions um and you're going to just

not and run some uh regressions. Um basically what I'm going to um you know these regressions I'm going to talk about are based on information for every

That's mostly the dependent variable in the regressions that I'll tell you about in a minute.

We have a lot of people who can do regressions.

our our quality and our repeatability and not have so many regressions and all

In these regressions, are you putting the ML, the output of the algorithm on the right hand side?

It's something that you kind of do after these nonparametric regressions as a post-processing type of thing to get estimates of treatment heterogeneity.

It's called the T-learner because you ran two regressions.

But if you were to do a panel regressions on developing countries, or globally, it's going to be a lot of data.

So why don't we try out a few other linear regressions where, for example, we by hand, create some of those features?

Which is the thing that sort of looks like running regressions, which is something that we do a lot of in the social sciences, and

overall governance quality and the foreign activity and we estimate our regressions using

now in the kind of third set of regressions what we can do is run both simultaneously we can ask well how much if you include both a

After that, we ran logistic regressions.

can do the statistical analysis, and run the regressions and see what the factors were that led to the success.

The summer learning loss is a term that they use to describe the regressions that kids in low-income neighborhoods face relative to their affluent peers.

that try to quantify this integrator detail this is essentially very standard regressions in the literature that have you know the

not zero so let me say it again the logic of assessed pricing regressions are very simple in bad times in the u.s u.s investors

I would have gone into a library and I would have run some regressions.

the, the calculations for simple regressions not too hard to do by hand.

And so we use that in my finance courses of people who do regressions and do performance analyses and risk complications and

And then we started building very simple predictive models, like logistic regressions or linear regressions, where we took essentially those face vectors for many people

A number of regressions that show that countries with open economies and a greater dependence on international trade, holding

he would take patients and take them back to their former lives; past life regressions.

Okay, so now the primary reason for this exercise is that they want to run regressions with it.

I was wondering if there's an analogous thing where if I use a transformer to classify something when I compute regressions or

That is we're going to need to first somehow estimate M hats and E hats using some first step regressions, this is what we did.

So far as I said, I focused on linear regressions, with regular risers given by limits on their coefficients.

and it is important to notice that this range of variation is ineffectively measured with ols estimates and that using os regressions

an inverse u and that can potentially explain why much of the prior empirical literature which is premised on linear regressions

basically no difference between goods that are affected and not affected by the tariffs over time um so we we did the password regressions