Change Details

Add a feature to detect outliers in a data set. See e.g. http://eurekastatistics.com/using-the-median-absolute-deviation-to-find-outliers http://eurekastatistics.com/using-mahalanobis-distance-to-find-outliers and the papers cited therein. Provide the access in the context menu of Column to this functionality. Open a dialog to show the found outliers and ask the user what to do with them: 1. mask them 2. remove them 3. do nothing

Add a feature to detect outliers in a data set. See e.g. http://eurekastatistics.com/using-the-median-absolute-deviation-to-find-outliers http://eurekastatistics.com/using-mahalanobis-distance-to-find-outliers http://www.itl.nist.gov/div898/handbook/eda/section3/eda35h.htm http://de.mathworks.com/help/curvefit/removing-outliers.html and the papers cited therein. Provide the access in the context menu of Column to this functionality. Open a dialog to show the found outliers and ask the user what to do with them: 1. mask them 2. remove them 3. do nothing Alternatively, finding of the outliers can be implemented as a new analysis function in the plot/curve.

Add a feature to detect outliers in a data set. See e.g. http://eurekastatistics.com/using-the-median-absolute-deviation-to-find-outliers http://eurekastatistics.com/using-mahalanobis-distance-to-find-outliers http://www.itl.nist.gov/div898/handbook/eda/section3/eda35h.htm http://de.mathworks.com/help/curvefit/removing-outliers.html and the papers cited therein. Provide the access in the context menu of Column to this functionality. Open a dialog to show the found outliers and ask the user what to do with them: 1. mask them 2. remove them 3. do nothing Alternatively, finding of the outliers can be implemented as a new analysis function in the plot/curve.