Abstract:
Outlier analysis is that the user do depends on the kinds data they have. An outlier is a data value, that has a very low probability of occurrence that is, it is unusual. There are three kinds of outlier detection in outlier analysis. This paper uses statistical approach in outlier analysis. The statistical approach to outlier detection assumes a distribution or probability model for the given data set. Therefore, this paper was distribution model for input statistical data in any fields and then identifies outliers by using Inter Quartile Range formula and hypothesis testing. Input data must be numerical data or statistical data. The case study in this paper is to find outlier detection for house selling price with two containing data set. The main objectives of this paper is to detect the fraud detection or inconsistent data, to trace whether outlier data are real or not and then to give decision markers in making better decisions.
