Regression Models

Choose a model type, set population coefficients, generate data, and fit via OLS or MLE.
Try it: Set the population parameters, click "Generate" to draw a sample, then "Fit" to estimate the model. Try small N (e.g., 20) vs large N (e.g., 500) — notice how the fitted curve (orange) tracks the population curve (teal dashed) more closely with more data. In the linear, quadratic, and cubic models, increase σ to see how noise obscures the signal; the logistic model has no σ, because the Bernoulli outcome carries its own variance.
Citation

Persson, B. N. (2026). Regression Models [Interactive visualization]. https://bjorn-persson.github.io/visualizations/regression/

@misc{Persson2026regression,
  author = {Björn N. Persson},
  year = {2026},
  title = {Regression Models},
  note = {Interactive visualization},
  url = {https://bjorn-persson.github.io/visualizations/regression/}}