The sampling error is the error one gets from observing a sample instead of the whole population. The bigger it is, the less faith you should have that your sample represents the true value in the population. If it is zero, your sample is VERY representative of the population and you can trust that your result is true of the population.
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we can find the zero error by closing the jaw of screw guage if the zero of main scale(MS) is concide with the zero of circular scale (CS) there is no zero error and if they are not concide there is a zero error in screw guage .
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Undefined: You cannot divide by zero
Yes, you MUST.
Variance is standard deviation squared. If standard deviation can be zero then the variance can obviously be zero because zero squared is still zero. The standard deviation is equal to the sum of the squares of each data point in your data set minus the mean, all that over n. The idea is that if all of your data points are the same then the mean will be the same as every data point. If the mean is the equal to every data point then the square of each point minus the mean would be zero. All of the squared values added up would still be zero. And zero divided by n is still zero. In this case the standard deviation would be zero. Short story short: if all of the points in a data set are equal than the variance will be zero. Yes the variance can be zero.