This report presents an integrated outlier detection method, which is named "An Approach to Detect Outlier by Integrating Univariate Outlier Detection and K-means Algorithm." It provides efficient outlier detection and data clustering capabilities in the presence of outliers, and based on filtering of the data after univariate analysis. This algorithm is divided into two stages. The first stage provides Univariate outlier analysis. The main objective of the second stage is an iterative removal of objects, which are far away from their cluster centroids by applying K-means algorithm. The...