The formula for calculating the standard error (or some call it the standard deviation) is almost the same as for the population; except the denominator in the equation is n-1, not N (n = number in your sample, N = number in population). See the formulas in the related link.
The standard deviation of the population. the standard deviation of the population.
Yes
No.
The true / real standard deviation ("the mean deviation from the mean so to say") which is present in the population (everyone / everything you want to describe when you draw conclusions)
They are statistical measures. For a set of observations of some random variable the mean is a measure of central tendency: a kind of measure which tells you around what value the observations are. The standard deviation is a measure of the spread around the mean.
The standard deviation of the population. the standard deviation of the population.
It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.
No.
Yes
The standard deviation if the data is a sample from a population is 7.7115; if it is the population the standard deviation is 7.0396.
If there is zero deviation all the observations are 50.
the sample standard deviation
The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.
There is no actual "smallest" observation - a standard deviation of zero means that all 100 of the observations had to be 46.
15
Yes.
A standard deviation of 0 implies all of the observations are equal. That is, there is no variation in the data.