343 templates · page 3 of 4
Mathematics diagram templates
Graphs, automata, Venn, set theory, lattices, function plots.
Math — Numerical Solution of ODEs
Euler and Runge–Kutta stepping.
LaTeX (KaTeX)Math — Lagrange Interpolation
Fitting a polynomial through given points.
LaTeX (KaTeX)Math — Moment Generating Functions
MGFs, moments and the PGF.
LaTeX (KaTeX)Math — Random Walks & Diffusion
Mean-square displacement of a random walk.
LaTeX (KaTeX)Math — KKT Conditions
Optimality with inequality constraints.
LaTeX (KaTeX)Math — Vector Spaces
Bases, dimension and rank–nullity.
LaTeX (KaTeX)Math — Applications of Calculus
What derivatives and integrals are used for.
Graphviz (DOT)Math — Choosing a Distribution
Matching a distribution to a situation.
Graphviz (DOT)Math — Area & Volume Formulas
Key mensuration formulas.
Graphviz (DOT)Math — Bisection Method
Bracketing a root and halving the interval.
LaTeX (KaTeX)Math — Taylor Remainder
The Lagrange form of the truncation error.
LaTeX (KaTeX)Math — Curvature
How sharply a curve bends.
LaTeX (KaTeX)Math — Centroids & Pappus
Centroid of a region and Pappus's theorem.
LaTeX (KaTeX)Math — Chi-square Test of Independence
Testing association in a contingency table.
LaTeX (KaTeX)Math — Least Squares (Normal Equations)
The matrix solution to linear regression.
LaTeX (KaTeX)Math — Big-O Complexity
Ordering common growth rates.
LaTeX (KaTeX)Math — Sorting Complexity
Time complexity of sorting algorithms.
LaTeX (KaTeX)Math — Shannon Entropy
Information content of a distribution.
LaTeX (KaTeX)Math — Huffman Coding
Optimal prefix-free compression.
LaTeX (KaTeX)Math — Karnaugh Maps
Minimising Boolean expressions.
LaTeX (KaTeX)Math — Dijkstra's Algorithm
Shortest paths from a source node.
LaTeX (KaTeX)Math — Principal Component Analysis
Dimensionality reduction by variance.
LaTeX (KaTeX)Math — Logistic Regression
Modelling a binary outcome.
LaTeX (KaTeX)Math — Neural Networks
Forward pass and learning by backpropagation.
LaTeX (KaTeX)Math — Classifier Metrics
Precision, recall and the F1 score.
LaTeX (KaTeX)Math — Monte Carlo Methods
Estimating integrals by random sampling.
LaTeX (KaTeX)Math — Hashing
Hash tables and their performance.
LaTeX (KaTeX)Math — Data Structures
Fundamental ways to organise data.
Graphviz (DOT)Math — Algorithm Paradigms
Major problem-solving strategies.
Graphviz (DOT)Math — Types of Machine Learning
The three broad ML paradigms.
Graphviz (DOT)Math — Computer Architecture
The von Neumann model.
Graphviz (DOT)Math — Network Layers (OSI)
The seven-layer OSI model.
Graphviz (DOT)Math — Survival Analysis
Kaplan–Meier estimator and hazard ratios.
LaTeX (KaTeX)Math — Relative Risk & Odds Ratio
Effect measures from a 2×2 table.
LaTeX (KaTeX)Math — Diagnostic Test Statistics
Sensitivity, specificity and predictive values.
LaTeX (KaTeX)Math — Number Needed to Treat
Translating risk reduction into NNT.
LaTeX (KaTeX)Math — Analysis of Variance
Comparing means of several groups.
LaTeX (KaTeX)Math — Multiple Regression
Several predictors and the fitted coefficients.
LaTeX (KaTeX)Math — Time Series
Decomposition and forecasting.
LaTeX (KaTeX)Math — Poisson Process
Random events in time.
LaTeX (KaTeX)Math — Critical Path Analysis
Scheduling project networks.
LaTeX (KaTeX)Math — Queuing Theory
Little's law and the M/M/1 queue.
LaTeX (KaTeX)Math — Decision Analysis
Expected value and the value of information.
LaTeX (KaTeX)Math — Statistical Process Control
Control limits for monitoring a process.
LaTeX (KaTeX)Math — Study Designs
Observational versus experimental studies.
Graphviz (DOT)Math — Sources of Bias
Common biases that distort studies.
Graphviz (DOT)Math — Choosing a Statistical Test
Matching a test to the data.
Graphviz (DOT)Math — Likelihood Ratio
Weighing evidence for competing hypotheses.
LaTeX (KaTeX)Math — Significant Figures
Rules for precision in calculations.
LaTeX (KaTeX)Math — Calibration Curves
Finding an unknown from a standard line.
LaTeX (KaTeX)Math — Detecting Outliers
Z-score and interquartile-range rules.
LaTeX (KaTeX)Math — Bootstrap Resampling
Estimating uncertainty by resampling.
LaTeX (KaTeX)Math — Effect Size
Cohen's d and the size of an effect.
LaTeX (KaTeX)Math — Meta-analysis
Pooling results across studies.
LaTeX (KaTeX)Math — Correlation vs Causation
Why association does not imply cause.
LaTeX (KaTeX)Math — Data-handling Cycle
The statistical investigation cycle.
Graphviz (DOT)Math — Variables in Experiments
Independent, dependent and control variables.
Graphviz (DOT)Math — Concept Map: Algebra
Core topics of school and college algebra.
Markmap (Markdown)Math — Concept Map: Calculus
Differentiation, integration and their uses.
Markmap (Markdown)Math — Concept Map: Geometry
Shape, space and trigonometry.
Markmap (Markdown)Math — Concept Map: Statistics
Describing data and making inferences.
Markmap (Markdown)Math — Newton-Raphson Method
Iterative root finding and its quadratic convergence.
LaTeX (KaTeX)Math — Nash Equilibrium
Best responses and mixed strategies in game theory.
LaTeX (KaTeX)Math — Chaos & the Logistic Map
Period doubling and the Lyapunov exponent.
LaTeX (KaTeX)Math — Complex Analysis
Cauchy-Riemann equations and contour integration.
LaTeX (KaTeX)Math — Calculus of Variations
The Euler-Lagrange equation for a functional.
LaTeX (KaTeX)Math — Convolution
The convolution integral and the convolution theorem.
LaTeX (KaTeX)Math — Causal DAG: Mediation
Direct and indirect (mediated) effects.
Causal DAGMath — Causal DAG: Selection Bias
Selecting on a common effect of exposure and outcome.
Causal DAGMath — Causal DAG: Instrumental Variable
An instrument affects the outcome only via the exposure.
Causal DAGMath — Causal DAG: Back-Door Path
A confounder opens a back-door path to be blocked.
Causal DAGMath — Causal DAG: Randomised Trial
Randomisation removes the arrow from confounders to treatment.
Causal DAGMath — Rational vs Irrational Numbers
Two kinds of real number.
Venn / EulerMath — Discrete vs Continuous Data
Two kinds of quantitative data.
Venn / EulerMath — Permutations vs Combinations
When order matters, and when it does not.
Venn / EulerMath — Vectors vs Scalars
Comparing the two kinds of quantity.
Venn / EulerMath — Prime vs Composite Numbers
Classifying integers greater than one.
Venn / EulerMath — Factors vs Multiples
Two related but opposite ideas.
Venn / EulerMath — Even vs Odd Numbers
The two parity classes of integers.
Venn / EulerMath — Causal DAG: Time-Varying Confounding
A confounder that is also affected by earlier treatment.
Causal DAGMath — Accuracy vs Precision
Two distinct ideas in measurement.
Venn / EulerMath — Qualitative vs Quantitative Data
The two broad kinds of data.
Venn / EulerMath — Area vs Perimeter
Two measures of a 2-D shape.
Venn / EulerMath — Similar vs Congruent Shapes
Two relationships between geometric figures.
Venn / EulerMath — Speed vs Velocity
Speed and velocity compared: a scalar rate and its vector counterpart.
Venn / EulerMath — Mean, Median & Mode
Choosing the right average.
Venn / EulerMath — Distance vs Displacement
Distance and displacement compared: a scalar path length and its vector counterpart.
Venn / EulerMath — Kinetic vs Potential Energy
The two great families of mechanical energy.
Venn / EulerMath — Mass vs Weight
A commonly confused pair.
Venn / EulerMath — Heat vs Temperature
Distinguishing thermal energy from its intensity.
Venn / EulerMath — Financial Mathematics
Compound interest, continuous growth and annuities.
LaTeX (KaTeX)Math — Set Theory
Set operations, De Morgan's laws and counting.
LaTeX (KaTeX)Math — Boolean Algebra
The laws of Boolean logic.
LaTeX (KaTeX)Math — Independent vs Dependent Variables
The two variable roles in an experiment.
Venn / EulerMath — Causal DAG: Simpson's Paradox
A confounder reverses an apparent effect.
Causal DAGMath — Causal DAG: Mediation vs Moderation
A mediator lies on the path; a moderator changes it.
Causal DAGMath — Velocity vs Acceleration
Two rates of change in kinematics.
Venn / EulerMath — Area vs Volume
2-D versus 3-D measures of size.
Venn / EulerMath — Fractions vs Percentages
Two ways to express proportions.
Venn / EulerMaths — Multiples of 3 vs 5
Common multiples are multiples of 15.
Venn / Euler