With the increased and vast use of online data, security in data mining has now become very important. Anonymity techniques have proved very useful in distributed computation. More techniques are still under research and improvements for achieving higher level of security in sensitive data. In this paper, we provide a review of the statistical Anonymization methods that can be applied for privacy preserving data mining. A brief evaluation is then made to point out the pros and cons of the same.