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Spotting the Odd: A Beginner’s Quiz on Outlier Detection and Treatment — Questions & Answers
This quiz contains 5 questions. Below is a complete reference of all questions, answer choices, and correct answers. You can use this section to review after taking the interactive quiz above.
Question 1: Identifying Outliers Using Standard Deviations
Which technique identifies outliers in a dataset as points lying more than 3 standard deviations from the mean, such as a test score of 100 when the class average is 60 and standard deviation is 10?
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Correct answer: A. Z-Score Method
Question 2: Treatment by Capping (Winsorization)
If high-income values above a certain threshold are replaced with the value at the 95th percentile, which outlier treatment technique is being used?
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Correct answer: B. Winsorization
Question 3: Visual Detection with Boxplots
When a data analyst uses a boxplot to visually detect outliers, which characteristic typically reveals an outlier, such as a dot or asterisk beyond the 'whiskers'?
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Correct answer: C. Points outside the whiskers
Question 4: Using the IQR Rule
Suppose a value in a dataset is below Q1 – 1.5×IQR or above Q3 + 1.5×IQR; which rule is being applied to flag outliers?
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Correct answer: C. Interquartile Range (IQR) Rule
Question 5: Imputing Outliers with Median Values
For a dataset containing an unusually high sensor reading due to an error, which treatment replaces this outlier by using the median value of the data?
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Correct answer: A. Median Imputation