Upper quartile
The upper quartile, or third quartile, is the value marking approximately the 75th percentile of an ordered dataset.
D3.js in Action, Third Edition
The 75th percentile is the value below which approximately 75 percent of an ordered dataset falls and is also called the third quartile.
- How it is used
- Uses the upper quartile to summarize and compare salary distributions in box plots and violin plots.
- How deep it goes
- Walks through computing the threshold with d3.scaleQuantile() and translating it into SVG box-plot geometry.
- Examples
- Uses women’s and men’s salary arrays for box plots and role-based salary distributions for violin plots.
- What you can do after
- Apply it via D3 to calculate an upper-quartile threshold and place box-plot or violin-plot summary marks.
Read how D3.js in Action, Third Edition explains upper quartile →
Statistics Slam Dunk
The upper quartile is the value marking approximately the 75th percentile of an ordered set of observations.
- How it is used
- Uses the 75% cutoff to summarize continuous NBA statistics and inspect distributions during exploratory data analysis.
- How deep it goes
- Defines the cutoff and relates it to the median of the upper half, without deriving alternative quartile algorithms.
- Examples
- Uses NBA draft ages and point-spread variables as concrete examples of upper-quartile reporting.
- What you can do after
- Evaluate continuous-variable distributions by reading upper-quartile output from summary() or SmartEDA.
Cyber Threat Hunting
The upper quartile is the value below which 75 percent of observations fall in an ordered dataset.
- How it is used
- Uses the upper quartile to bound an interquartile filter for noisy connection-timing analysis.
- How deep it goes
- Defines the 75% boundary and applies it in an IQR workflow, stopping short of deriving quartile calculation methods.
- Examples
- Demonstrates upper-quartile filtering on time_diff_sec values from grouped network connection records.
- What you can do after
- Diagnose noisy connection timing by filtering values outside quartile boundaries before calculating variability.
Related concepts
- quantileskind of · A quantile is a value that divides an ordered dataset or probability distribution so that a specified proportion of observations lies at or below it.
- quartilekind of · A quartile is a quantile or cut point that divides ordered observations into four approximately equal parts.
- percentileequivalent to · A percentile is a value in an ordered distribution at or below which a specified proportion of observations falls.
- interquartile rangeused by · The interquartile range is the difference between the third and first quartiles of a distribution, measuring the spread of its middle half.
- quantile quantizationused by · Quantile quantization transforms numerical values into discrete levels or buckets using thresholds derived from the values’ distribution quantiles.
- box-and-whisker plotused by · A box-and-whisker plot is a statistical graphic that summarizes a numerical distribution using quartiles, a median, and whiskers or markers indicating spread and potential outliers.
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