It measures the error or variability in predicting Y.

It is found by calculating SSR/SS total

Standard error of the sample mean is calculated dividing the the sample estimate of population standard deviation ("sample standard deviation") by the square root of sample size.

Standard error is an indicator of the expected level of variation from the predicted outcome in an estimate. So even though the mean is mostly likely the outcome, the actual range the outcome could call into is a region which is measured by the standard error.

From what ive gathered standard error is how relative to the population some data is, such as how relative an answer is to men or to women. The lower the standard error the more meaningful to the population the data is.

Standard deviation is how different sets of data vary between each other, sort of like the mean.

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Not true!

Standard deviation is a property of the whole population or distribution. Standard error applies to a sample taken from the population and is an estimate for the standard deviation.