So many choices! Prism's nonlinear regression dialog has ten tabs (eleven if performed from the multiple variables data table), and can seem overwhelming at first. But you don't have to learn about all the choices when you first fit a curve.

If your goal is to fit a standard curve from which to interpolate unknown values

If your goal is to interpolate from a standard curve, you can ignore most of the choices that Prism offers. You do need to pick a model, but you should judge the adequacy of the model visually. If it goes through the points without wiggling too much, it is fine for interpolation. Note that Prism offers a simplified curve fitting analysis for interpolation.

If your goal is to fit a model to determine best-fit parameters

If your goal is to fit a model to determine parameter values, then choosing a model is the essential first step. You should not expect a computer (or a software company's tech support) to choose a model for you. Choosing a model, and deciding which parameters should be constrained and which should be shared among data sets, is a scientific decision that is fundamental to analyzing your data. The other choices are useful, but can be put aside when you are first learning curve fitting.

Should you use an XY table or a Multiple Variables table?

Before you even get to the analysis dialog, you need to decide which table format to use for your data. This is an essential choice that affects how you organize your data and assign variables.

Use a Multiple Variables table when you're importing data from plate readers or databases, when you have many curves to fit (especially with multiple experimental factors), or when your data is already in long "tidy" format with one row per observation. Multiple Variables tables excel at handling complex experimental designs where you're fitting curves across combinations of factors like compound × cell line × timepoint.

Use a traditional XY table when you're entering data directly into Prism for a small number of curves (typically 2-10 datasets), or when your data naturally comes in side-by-side column format. XY tables are intuitive and straightforward for simple curve fitting projects.

The curve fitting itself is identical regardless of table format - same equations, same parameters, same results. The difference is just in how you organize and assign your data. For detailed guidance on using Multiple Variables tables for nonlinear regression, see Running Nonlinear Regression from Multiple Variables Data Tables.