Summary statistics, outliers, missing value strategies, distributions, correlations, data types and cleaning checklists.
41 cards · basic cards · AI-written, checked twice. Edit anything.
- What is the mean?
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The average of all values in a dataset, calculated as the sum divided by the count.- What is the median?
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The middle value when data is sorted in order; the 50th percentile.- What is the mode?
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The value that appears most frequently in a dataset.- What is standard deviation?
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A measure of how spread out data points are from the mean.- What is variance?
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The average of squared deviations from the mean; the square of standard deviation.- Define the interquartile range (IQR).
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The range between the first and third quartiles (Q1 and Q3), containing the middle 50% of data.- What is a percentile?
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A value below which a given percentage of data points fall.- What is an outlier?
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A data point that is significantly different from other observations in the dataset.- What is the IQR method for detecting outliers?
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Values below Q1 - 1.5(IQR) or above Q3 + 1.5(IQR) are flagged as outliers.- What is the Z-score method for outliers?
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Points with Z-score greater than 3 or less than -3 are typically considered outliers.- Name three strategies for handling outliers.
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Remove them, cap them at a threshold, or transform the data.- What are the three types of missing data patterns?
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MCAR (Missing Completely at Random), MAR (Missing at Random), and MNAR (Missing Not at Random).- What is MCAR (Missing Completely at Random)?
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Missing data has no relationship to observed or unobserved values; missingness is purely random.- What is MAR (Missing at Random)?
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Missingness depends on observed data but not on the missing values themselves.- What is MNAR (Missing Not at Random)?
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Missingness depends on the unobserved values themselves; the most problematic pattern.
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