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How do you find the beginning value for an outlier?
Multiplying the interquartile range (IQR) by 1.5 will give us a way to determine whether a certain value is an outlier. If we subtract 1.5 x IQR from the first quartile, any data values that are less than this number are considered outliers.
How else would you determine outliers?
Using the Interquartile Range to Create Outlier Fences. You can use the interquartile range (IQR), several quartile values, and an adjustment factor to calculate boundaries for what constitutes minor and major outliers. Minor and major denote the unusualness of the outlier relative to the overall distribution of values …
How can I replace outliers with maximum non-outlier value?
When I detect outliers for a variable, I know that the value should be whatever the highest non-outlier value is (i.e., the max if there were no outliers). How can I impute this value in python or sklearn? I guess I can remove the values, get the max, replace the outliers and bring them back. But hoping there’s a function for that already.
Are there a lot of outliers in your data?
There are a lot of outliers. Outliers are rare by definition. If, for example, 30% of your data is outliers, then it actually means that there’s something interesting going on with your data that you need to look further into. It changes your results.
Is it better to make assumptions or outliers?
This can make assumptions work better if the outlier is a dependent variable and can reduce the impact of a single point if the outlier is an independent variable. Another option is to try a different model. This should be done with caution, but it may be that a non-linear model fits better.
How to identify and address outliers in decision making?
Codes for the categories are 2 = 0 to 2 years of experience, 4 = 3 to 4 years of experience, 6 = 5 to 6 years of experience, 8 = 7 to 8 years of experience, 10 = 9 to 10 years of experience, and so on until the final code of 32 = 31 years of experience or more. Identifying and Addressing Outliers 83 C. Planning and Decision Making