The performance of three rules for dealing with outliers in small samples of size n from the normal distributionN(μ, σ2) is investigated when the primary objective of sampling is to obtain an accurate estimate of σ2. It is assumed that at most one observation in the sample may be biased, arising from eitherN(μ + aσ, σ2) orN(μ, (1 +b) σ2). Performance of each rule is measured in terms of “Protection”, the fractional decrease in MSE obtained by using the rule when a biased observation actually is present in the sample. Numerical results have been obtained forn5 ≤ 11 when μ is known andn= 3 when μ is unknown.