Sample variance is a measure of how much the data values in a sample deviate from the sample mean, while population variance is a measure of how much the data values in a population deviate from the population mean.
Sample variance is calculated by taking the sum of the squared differences between each data value and the sample mean, and then dividing by the sample size minus one.
Calculating sample variance allows us to measure the spread or variability of a data set. It is useful in understanding how much the data values differ from the average and in making comparisons between different samples.
No, sample variance cannot be negative. It is always a non-negative value, as it is calculated by squaring the differences between data values and the sample mean.
Standard deviation is the square root of variance. It is often used as a more intuitive measure of variability, as it is expressed in the same units as the data. It is calculated by taking the square root of variance, and can also be used to measure the spread or variability of a data set.