Hobnob was positively skewed. Foreplay, was, negatively skewed.

The positively skewed for HobNob. The negatively skewed for FourPlay.

This will be so skewed.

John. Focustesting showed Johnny skewed a little young.

If they're slightly skewed, we'll see a different image.

It's a little bit more skewed looking like this.

So, that's positively skewed. Four Play is the opposite.

You get kind of a more and more skewed ellipse.

This gives you a sense of how skewed the power structure.

Because the arithmetic mean was skewed by this, what they call an outlier.

Also, the working memory score. Not quite as bad, but still sort of skewed.

And at some point, the ellipse keeps getting more and more skewed like that.

And so it's not surprising that we have a negatively skewed distribution with respect to SAT scores.

And those distributions are notoriously positively skewed within an individual. Because on some trials just moment to moment.

So, for Hobnob, there were just a few raters, who really liked it. So, that's why it was skewed.

So, think about it this way if you've got an artificial constraint, artificial constraints lead to arbitrary distinctions and a skewed worldview.

The median is really good if you have some kind of crazy number out here that could have otherwise skewed the arithmetic mean.

Central tendency will typically rely on the mean or average. Sometimes we'll use the median when we have extreme scores or skewed distributions.

Um, so, it was negatively skewed. I can show that, show those distributions instead of me awkwardly drawing with the stylus, I, I promise to get better.

Some of the problems that I think we are having is that there are a lot of numbers that are being skewed and we need to have somebody there that is going to make the changes.

Concretely if you instead define the feature X one to be the size of the house divided by two thousand, and define X two to be maybe the number of bedrooms divided by five, then the count well as of the cost function J can become much more, much less skewed so the contours may look more like circles.

I'm going to ignore theta zero, so let's about theta 0 and pretend as a function of only theta 1 and theta 2, but if x1 can take on them, you know, much larger range of values and x2 It turns out that the contours of the cause function J of theta can take on this very very skewed elliptical shape, except that with the so 2000 to 5 ratio, it can be even more secure.

What makes it even a little bit more skewed because it's winner takes all and the candidates aren't silly and they wanna make sure that they spend their money and their visits and their time in the most leverageable way it actually creates this weird scenario where candidates will often ignore huge part of the population and they ignore them because those huge parts of the population are unlikely to swing either one way or the other.