- Why square instead of absolute value?
- Why square the difference in standard deviation?
- Why do we square the differences from the expected value?
- What is the difference between absolute and relative path in Java?
Why square instead of absolute value?
Having a square as opposed to the absolute value function gives a nice continuous and differentiable function (absolute value is not differentiable at 0) - which makes it the natural choice, especially in the context of estimation and regression analysis.
Why square the difference in standard deviation?
The variance is defined as the average squared difference of the scores from the mean. We square the deviation scores because, as we saw in the Sum of Squares table, the sum of raw deviations is always 0, and there's nothing we can do mathematically without changing that.
Why do we square the differences from the expected value?
The main reason for squaring the values of difference is to keep the values of distance from the mean to be positive. e.g. say we have a data set of x coordinates as [-2, -1, 0, 1, 2]. The Mean here is 0. So if we take the sum distance of the points from the mean.
What is the difference between absolute and relative path in Java?
A path can be absolute or relative. An absolute path contains the full path from the root of the file system down to the file or directory it points to. A relative path contains the path to the file or directory relative to some other path.