Median
The median is the middle value of an ordered set of observations, or the mean of the two middle values when the set has an even number of observations.
Statistics Slam Dunk
The median is the middle value of an ordered set of observations, or the midpoint of the two middle values when the count is even.
- How it is used
- Uses the median to describe typical NBA performance, compare groups, and assess whether outliers distort the mean.
- How deep it goes
- Defines calculation, demonstrates grouped R summaries, and interprets plots; stops short of formal derivations.
- Examples
- Demonstrates draft-segment career games, team points distributions, and standardized wins shown through boxplots.
- What you can do after
- Apply it via base R, dplyr, and ggplot2 to summarize groups and interpret NBA distributions.
Pandas Workout: 200 exercises to make you a stronger data analyst
The median is the middle value of an ordered set of numerical values, with averaging of the two middle values when the set has even size.
- How it is used
- Uses the median as a robust central value within pandas descriptive-statistics analysis.
- How deep it goes
- Explains ordering, even-sized sets, quantile equivalence, and outlier behavior, but stops short of implementation internals.
- Examples
- Uses normally distributed Series, modified minima, taxi passenger quantiles, and city-growth comparisons.
- What you can do after
- Apply it via pandas Series.median() or quantile(0.5), then compare the result with the mean when outliers matter.
Read how Pandas Workout: 200 exercises to make you a stronger data analyst explains median →
Effective Data Analysis
The median is the middle value of an ordered dataset, or the average of the two middle values when the dataset has even size.
- How it is used
- Reports a typical data position, especially for skewed or asymmetrical distributions and stakeholder-facing summaries.
- How deep it goes
- Explains central tendency, outlier robustness, distribution assumptions, and reporting trade-offs, but does not develop formal derivations.
- Examples
- Uses an outlier replacement comparison, sleep and interruption summaries, distribution figures, and a Python-generated exercise.
- What you can do after
- Evaluate whether the median is an appropriate stakeholder metric for a dataset’s shape and outlier profile.
D3.js in Action, Third Edition
The median is the middle value of an ordered dataset, or the midpoint between the two middle values when the dataset has an even size.
- How it is used
- Highlights the center of a distribution in box plots and supports comparisons between salary groups.
- How deep it goes
- Defines the median as the 50th percentile and demonstrates D3 calculation and SVG placement without deriving the statistic.
- Examples
- Uses women’s and men’s salary arrays from a data-visualization survey and compares their medians in box plots.
- What you can do after
- Builds a median calculation and visualizes it with D3 and SVG box-plot elements.
Advanced Algorithms and Data Structures
A median is a middle-ranked value that divides an ordered collection into lower and higher portions.
- How it is used
- Builds balanced k-d trees by selecting middle-ranked coordinate values as recursive pivots.
- How deep it goes
- Explains recursive coordinate-aware partitioning and stops short of general median-selection internals.
- Examples
- Uses two-dimensional point partitions, pseudocode, and construction recurrences as concrete examples.
- What you can do after
- Build a balanced k-d tree from a known point set using recursive median partitioning.
Read how Advanced Algorithms and Data Structures explains median →
Grokking Statistics
The middle value of an ordered set of observations, or the midpoint of the two middle values when the set has even size.
- How it is used
- Summarizes the typical value in numerical data, especially when extreme observations make the mean misleading.
- How deep it goes
- Defines ordered selection and even-size averaging, then demonstrates outlier resistance with a worked calculation.
- Examples
- Uses ordered number lists and bar tabs containing a $1,500 outlier to compare median with mean.
- What you can do after
- Apply it via NumPy and interpret whether the median better represents a typical observation than the mean.
Grokking Machine Learning
The median is the middle value of an ordered set of values, or the average of the two middle values when the set has even size.
- How it is used
- Uses the median to fill missing numeric values without deleting a useful dataset column.
- How deep it goes
- Applies the median through a concrete missing-data workflow but does not develop its mathematical calculation.
- Examples
- Demonstrates replacing 177 missing Age values with the calculated median of 28 in an 891-row dataset.
- What you can do after
- Apply it via median and fillna functions to replace missing numeric entries.
Related concepts
- point forecastuses · A point forecast is a prediction that assigns a single value to each future observation without representing forecast uncertainty.
- meancontrasts with · A mean is a measure of central tendency, calculated as the arithmetic average of values or, for a random variable, as the probability-weighted average of its possible values.
- descriptive statisticskind of · Descriptive statistics are methods for summarizing and characterizing observed data without drawing conclusions beyond those data.
- mean absolute errorused by · Mean absolute error is the arithmetic mean of the absolute differences between corresponding predicted and reference numerical values.
- data aggregationkind of · Data aggregation is the combination of multiple values, records, observations, or results into a consolidated or summarized output.
- quantilesequivalent to · 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.
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