Flashcard: Data Modeling and Curve Fitting Techniques — 10 carte

Model fit — goal?

Choose the model that best describes data, minimizing errors.

Model fit — goal?

Minimize distance between model and data points.

Point cloud — representation?

A set of spatial data points in 2D or 3D space.

Scatter plot — purpose?

Visualize data distribution and relationships.

Curve fitting — methods?

Using models like linear, polynomial, logarithmic, or exponential to approximate data.

R² — what?

Proportion of variance explained by model.

Affine model — form?

y = a + bx.

Polynomial model — degree?

Degree 2, 3, etc.

Logarithmic fit — formula?

y = log(a x) + b.

Interpolation — definition?

Estimate within data range.