The standard error is the difference between a mean and the value you would expect based on the standard deviation of your data. In this case, we’re talking about a mean of 0.10 and a standard deviation of 0.5.
The same applies to the values between the mean of 0.4 and 0.5, as well as the values between 0.1 and 0.2.
The reason that the standard deviation is so small isn’t because it’s too low to be a good approximation of the mean, but rather because it’s a relatively small error. And the mean is not as “small” as you’d expect. The standard deviation is actually the difference between the mean and the average of the data, but you don’t want to make it so small. If you want to reduce the standard deviation, you have to go down the standard deviation again.
There’s a reason why you can’t just take the mean of the data and compare it with the standard deviation. When you’re talking about a very small number, such as a standard deviation, the mean of the data is a very good approximation of the true mean. But when you’re talking about a number that’s just a few points higher or lower than the mean, a standard deviation is the best you can do.
And that’s why matlab uses the mean of the data for this.
It can be confusing because the mean isn’t the same thing as the standard deviation. When you’re talking about a small number, such as a standard deviation, the standard deviation is a better approximation of the true mean because it has fewer degrees of freedom. But when you’re talking about a number thats just a few points higher or lower than the mean, a standard deviation is the best you can do.
And you use the mean to make your life easier too. When you use the mean of a data set to find the standard deviation for a data set, you end up with the mean of the whole data set.
So matlab is saying that each data point in the graph has an error that is exactly the same size as the standard deviation. But then matlab uses the mean to find the standard deviation of the whole set of data points. Thus matlab is saying that the standard error of a data point is the size of the standard deviation of that data point divided by the size of the standard deviation of the whole set of data points. Which is basically the same thing as the standard error of the mean.
The original code actually started it on 8-bit/64 bit CPU. This is the way Matlab goes in Matlab. The original code didn’t work because 8-bit/64 bit CPU was so much slower than 64-bit. So it was called a “time variable”.
The original code started with a bit of time variable. However, we got to that bit later. This time it was the time variable that is really important, and we found out that it actually took less than 4 seconds to run the code. Which was really cool because it took just 4 seconds to run the code.