Comparing two estimators.

Q: Suppose we take a random sample of size n from a N (0,1) populations. Consider two estimators of simga squared.

Two estimators equations and tables can be seen here:

Compare of s^2 and SM^2 for their bias, variances and MSE.

I don't really know how to approach this problem. How can there be negative bias?
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Ambassador to the humans
Bias is just "expected value of the estimator - True value of the parameter". If the estimator under estimates the true parameter (on average) it has negative bias.
Okay thanks! So does a value closer to 0 means there is less bias and the larger value of variance means its more variable? and for MSE, shouldn't a lower value indicate less error?

I know that when n increases the s2 and S^2M becomes more similar due to the central limit therom.