How does Z-score outlier detection work?
An example of an AI chatbot conversation about Z-score outlier detection in statistics.
Can you explain how Z-score outlier detection works?
Sure! Z-score outlier detection identifies outliers by measuring how far a data point is from the mean in terms of standard deviations.
How do you calculate the Z-score for a data point?
The Z-score is calculated using the formula: Z = (X - μ) / σ, where X is the data point, μ is the mean, and σ is the standard deviation.
What Z-score value indicates an outlier?
Typically, a Z-score above 3 or below -3 is considered an outlier, but this can vary based on the context.
Are there any limitations to using Z-score for outlier detection?
Yes, Z-score assumes a normal distribution of data, so it may not be effective for skewed distributions.
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