Now what happens when you change the standard deviation.

We have very good data since 1962 1960 about on the size of families in all countries.

And I'll just call this, what's the probability that I land between 1 standard deviation the mean is minus 5 one standard deviation below the mean is minus 15 and one standard deviation above the mean is 10 plus minus 5 is 5.

In particular, consider a single data item as our sequence.

It's the quadratic deviation from the mean.

It should also produce descriptive statistics that look like this. Again, these are from

And so, you know, the variance, I'm gonna estimate as just the average of the square differences, between my examples, minus the mean.

One minute, 26.5 seconds 108.5 miles an hour.

Test are just the average squared error, or one half of the average squared error on my training validation and test sets without the extra regularization chart.

What are the mean and standard deviation of this distribution of the distance between the initial position and the final position?

To show ourselves this, let's just redo the calculation.

95. 1 miles an hour.

Delayed Trap

I've got in my example minus the mean, minus the center, minus the mean of distribution.

Remember, every sample statistic is just a point estimate.

There's variance in the sample SD squared.

If 1 is the outcome, here is our difference from the mean we square this.

Can you guess what the effect is of adding 1000 to your salary on the mean and the standard deviation?

The variance by its very nature computes in the quadratic.

This is what factory workers earn in an hour in Indonesia on average, 20 cents.

I've got a bad case of jet lag.

Notice that this method will also reveal the bias in the wand measurement.

looked at different types of histograms to get the feel of different shapes of distributions.

From the mean to one standard deviation above, and one standard deviation below.

I know that's a mouthful. So, you might wanna replay that.

These were the results for Jeremy Lin.

dividing Guttermeg's principle of opposing forces in motion, and adjusting for the difference in equilibrium...

Mu is the mean, or the average.

Z scores, then we know what percentage of scores fall in certain ranges.

T statistic from this.

You evaluate it at plus 5, which is right here.

So it's just e to the, this whole thing over here, minus x minus the mean squared over 2 sigma squared.

What happens if there's no correlation?

I don't know.

But there are huge differences at the same time between the better off countries and the worse off countries and there are also huge inequalities within countries.

We average 8 hour's work a day.

So there are the descriptive statistics, or summary statistics.

Let's practice this. I'll give you a couple of quizzes now.

So the mean for this sample is 5.47, the mean for the population was 5.5.

How did we keep track of time without a clock?

It's jet lag.

My shooting hand. Got some jet lag so...

To see this, recall that a is equal to y bar b x bar, but for a standard score, zₓ always has a mean of 0 and zᵧ has a mean of 0, because we subtracted out their means.

Here is an interesting data sequence 3, 3, 3, 3, 3.

In fact, every element over here is 5 times as large as any element over here. Now, how does this affect the variance?