Примери за използване на Sampling distribution на Английски и техните преводи на Български
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So this is the sampling distribution.
The sampling distribution of the sample mean.
So this is the sampling distribution.
The sampling distribution of the sample mean.
So this is the sampling distribution.
And then we divide that by the standard deviation of the sampling distribution.
You had your sampling distribution of the sample mean.
Now, what is the standard deviation of our sampling distribution?
Let's take the sampling distribution of the sample mean.
We divide that by the standard deviation of the sampling distribution.
So this is the sampling distribution of the sample mean.
So this is 2.5 times the standard deviation of the sampling distribution.
It's the sampling distribution of the sample mean.
As a sample from the sampling distribution.
And this is a sampling distribution of the sample mean for n is equal to 7.
We don't actually know the standard deviation of the sampling distribution.
So I will call this the sampling distribution of this statistic, of P1 minus P2.
We don't know the actual standard deviation of the sampling distribution.
So let's think about the sampling distribution of the sample mean of x.
Where it's equivalent to taking a sample from the sampling distribution.
So let's say we have a sampling distribution of the sample mean right here.
It has some mean,so this is your mean of your sampling distribution still.
And the sampling distribution's standard deviation, so the standard deviation of the sampling distribution, so we could view that as one standard deviation right over there.
It is a sample from the sampling distribution of the sample mean.
Now if you do a one-tailed test like this, what we're thinking about is, what we want to look at is, all right,we have our sampling distribution.
To think about that let's just think about the sampling distribution if we assume the null hypothesis.
And especially because the proportions that we're dealing with aren't close to one or zero, andwe have a large sample size, the sampling distribution will be approximately normal.
And we know that the mean of the sampling distribution, that the means of all of your means, or of the actual distribution of means, is actually going to be your original population mean.
And we can specify that by the standard deviation of the sampling distribution of the means.