Finding Outliers using Interquartile Range | Statistics, IQR, Quartiles

Описание: How do we find outliers of a data set using the interquartile range? This is done using a simple rule, any value less than Q1-1.5*IQR is an outlier, and any value greater than Q3+1.5*IQR is an outlier. We'll go through the step by step process of finding outliers using IQR in today's video statistics lesson! #Statistics #APStats

Remember that a data value being an outlier doesn't suggest we should discard it; it means we should take a close look at it and decide what to do in our statistical analysis. We may want to discard it, it may be an error/typo in which case we would want to correct it if possible, or it may be a key to understanding the situation being analyzed!

Also, remember that if this rule doesn't identify a value as an outlier - that doesn't mean YOU don't think it is an outlier. If a data set is sufficiently small you can look at each value individually and determine what values merit special attention. This rule for outliers is particularly useful for large data sets; but we apply it to small data sets so we can practice applying it by hand and seeing it in action!

Interquartile Range vs Range of a Data Set:    • IQR vs Range (interquartile range vs range...  

I hope you find this video helpful, and be sure to ask any questions down in the comments!

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