Logistic growth
How does density dependence change exponential growth?
Start experiment ↓Interactive teaching examples
Fourteen interactive experiments connect equations to behaviour, inference, and decision. Choose by purpose, then change one assumption and inspect what survives.
Model finder
Use the two filters or scan the research questions. Every result links directly to the corresponding interactive workbench.
How does density dependence change exponential growth?
Start experiment ↓How do intervention timing and strength reshape an epidemic curve?
Start experiment ↓Why does risk grow faster than speed?
Start experiment ↓When does gradual pressure trigger an abrupt and path-dependent change?
Start experiment →Can a governing equation be recovered from noisy observations?
Start experiment →How can local alignment create global order without a leader?
Start experiment →What changes when groups, rather than only pairs, transmit influence?
Start experiment →What must a reusable model learn to map one function into another?
Start experiment →Which shapes survive a change of observational scale?
Start experiment →Can blur, pixel size, or segmentation-boundary displacement create a spanning threshold that is absent from the latent field?
Start experiment →When should an ageing entangled pair be discarded rather than retained?
Start experiment →Can the data distinguish the parameters that produced them?
Start inquiry →What is a treatment effect when one unit changes another?
Start inquiry →Which decision survives a plausible probability shift?
Start inquiry →Showing all 14 experiments.
01 · Discrete dynamics
The growth term is large when the population is small, then weakens as the state approaches the carrying capacity K. A larger growth rate can create overshoot and alternating corrections.
02 · Coupled differential equations
The model divides a fixed population of 1,000 into susceptible, infectious, and removed groups. On the selected intervention day, transmission β is reduced by the chosen percentage.
This is a deliberately simplified teaching model, not an epidemiological forecast or medical recommendation.
03 · Scaling and decomposition
Reaction distance grows linearly with speed; braking distance grows quadratically. The decomposition shows why a modest increase in speed can create a much larger increase in total distance.
The formula is a classroom baseline on a level road with constant friction. Real stopping distance also depends on gradient, tyres, brakes, weather, perception, and driver behaviour.
From interaction to evidence
Use each example to record one prediction, one parameter change, one observed response, and one limitation. That four-line record turns exploration into a small modeling experiment.
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