(Excel and R will be referenced heavily here, though SAS, Python, etc., all work).
Unfortunately, resisting the temptation to remove outliers inappropriately can be difficult. Most parametric statistics, like means, standard deviations, and correlations, and every statistic based on these, are highly sensitive to outliers. From what I've seen in workbooks over the years, SUM is the most frequently used Excel function, and AVERAGE is the runner-up.

The Data Mining Client for Excel helps you detect this data, and then update the values or suppress them. Exclude the Outliers Last week, a client asked about excluding some of the highest and lowest numbers from … Continue reading "Ignore Outliers with Excel TRIMMEAN"

For example, even after removing the extreme max and min in a timeseries, I still want to see the entire timeseries but with the outliers removed or changed to a null value.
See attachment. How can I select or simply remove all the outliers from this data matrix, leaving the rest of the data in tact? Press the delete-button on the keyboard.

In Excel, select the cell contaning the "outlier".

And since the assumptions of common statistical procedures, like linear regression and ANOVA, are also […]

I'm creating an Excel Scatter Chart for plotting the intersect of two variables from a list on a different worksheet. It’s essential to understand how outliers occur and whether they might happen again as a normal part of the process or study area. I have looked on about every google tutorial there is, and either the author includes an estimation rather than a statistical calculation or the formula itself just trims data rather than finding true outliers.

... You have to use plot beween X value and Y value in excell program cause by checking variation. Handling Outliers. In testing, I've noticed that an outlier plot can really shift the scatter distribution.

For example, you can replace outliers with an arithmetic mean, or you can delete rows that contain potentially wrong values. I know I can go to the data set and remove the outliers but want to simplify by doing it on the graph. Two of the most common graphical ways of detecting outliers are the boxplot and the scatterplot.

When viewing some graphs, sometimes I need to ignore some outliers. Like to know whether it is possible to click on the outlier data or the corresponding x on the x axis and the graph will be updated without this outlier data. The Remove Outliers wizard gives you several tools to handle outliers appropriately:

Outliers are one of those statistical issues that everyone knows about, but most people aren’t sure how to deal with. Outliers can be very informative about the subject-area and data collection process.

Would you agree, or do you see other functions used more often than those two? If I switch to the worksheet with the underlying data, I can resolve the issue (for my purposes) by using the built in Filter. As such, outliers are often detected through graphical means, though you can also do so by a variety of statistical methods using your favorite tool. I need to analyze hundreds of data sets and remove the statistical outliers, so that the reported slopes are statistically accurate.

I need to scrub the data, then analyze it, in a separate step.

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