Regime type and foreign direct investment article in quarterly journal of political science 42 march 2009 with 888 reads how we measure reads. Koether hampdensydney college residual analysis and outliers. The cd r thus pr ovides a useful alternative to existing methods for detec ting outliers in structured datasets. The treatment of outliers and influential observations in. After viewing the box plot, a potential outlier might be identified. Pdf on the detection of influential outliers in linear. This is a sign that the outliers have dragged down the fitted line. Consequentially, when outliers are present in a dataset, it leads to misleading results. Outline 1 introduction 2 residual analysis 3 nonlinear regression 4 outliers and in. Types of outliers in linear regression introduction to. This paper introduces the robustreg procedure, which is experimental in sasstat. The effects of outliers on regression analysis are discussed, and examples of various detection methods are given.
Residual analysis and outliers hampdensydney college. This is a measure of how unusual the x value of a point is, relative to the x observations as a whole. Determining outliers with linear regression equations duration. When outliers are present in the data, trimmed means are robust estimators of the population mean that are relatively insensitive to the outlying values. If the upper and lower 5% of the data are removed, then it creates a 10% trimmed mean.
Outliers, durbinwatson and interactions for regression in spss. It can be used to detect outliers and to provide re sistant stable results in the presence of outliers. Pdf regression analysis for data containing outliers and high. Regression analysis, as we know, is one of the most important statistical techniques for model fitting. Detection of outliers in regression model for medical data. Assessing the impact of an outlier in a simple regression. A similar plot forx 2 is constructed by regressingy on x l and x 2 on x l and graphing. Pdf five detection of outliers procedures in multiple regression.
Another problem is that the residuals indicate an overall upward trend. Leverage of a point has an absolute minimum of 1n, and we can see that the red point is right in the middle of the points on the x axis, and has a residual of 0. Outliers in regression are observations that fall far from the cloud of points. Robust regression is an important tool for analyz ing data that are contaminated with outliers. Examples of various outliers found in regression analysis. These points are especially important because they can have a strong in. The treatment of outliers and influential observations in regression. On the detection of influential outliers in linear. If a regression model is appropriately selected, most observations should be fairly close to the regression line or hyperplane. Strategies for detecting outliers in regression analysis.
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