UPCOMING WEBINAR: From Thousands of Tables To One Clear Story: using AI in survey analysis During the data cleaning process, you may find outliers in your Numeric data. You can cap these low/high outliers or treat those values as missing data automatically for the variables you select. This article describes how to recode a numeric variable containing high or low outlier values:
To one where those outliers are excluded from reporting and analyses:
Requirements
- Numeric variable(s) containing high or low outlier values that you want to recode as missing values.
Method
1. From the Data Sources tree, select your Numeric variable(s), or select the data set name to do this for all numeric variables in the data set.
2. From the toolbar, go to Anything > Data > Variables > Modify > Recode > and then select one of the following depending on whether you want to set high or low values as missing:
- Set High Values to Missing in Numeric Variable(s).
- Set Low Values to Missing in Numeric Variable(s).
3. Enter the value that you want to use as the cutoff, similar to the high values cut-off dialog below:
Next
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