About XY data tables

In an XY table every point is defined by both an X and a Y value. This kind of data are often fit with linear or nonlinear regression.

Don't use an XY table if you want to make a survival table. In a survival table, instead of entering Y values to be plotted, you enter codes designating survival or censored for each subject.

•	Subcolumns are for replicates in a treatment group. Prism uses these to calculate error bars.

•	Blue italics values are “excluded” (ignored by analyses and graphs). Use the button from the Change toolbar or select Edit Menu.. Exclude Values

•	Row titles can be used to label individual subjects or samples.

For XY graphs, you can either enter error values that you have calculated elsewhere, or Prism will calculate error bars from your raw data.

•	If you want Prism to calculate your error bars, tell Prism how many replicates you have for each subject.

•	Prism will create a data table with that number of subcolumns for you to enter your data. Enter your replicates in side-by-side columns.

•	Prism can create subcolumns formatted for error values computed elsewhere:

Prism can also plot horizontal X error bars. You must enter X error values directly; Prism cannot compute them.

If you want to plot a graph with symbols, but you want to enter a sequence of category names instead of numerical X values, use a two grouping variable table instead of an XY table.

Each data table has a single column for X and up to 104 sets of Y values. What should you do if you have different X values for each set of Y values? There are two ways to solve this problem.

The best approach is to stagger the data entry. You don't have to start entering data in the first row. This example shows three data sets with different X values.

An alternative approach is to enter each data set on a different table. The disadvantage with this method is that you lose some analysis choices. You must enter all the data sets on one table in order for Prism to compare linear regression lines, to compare best-fit values from nonlinear regression, and to compare survival curves. Another minor disadvantage is that Prism will automatically make a different graph for each table. However, you can delete the unneeded graphs and include data from all the data tables on a single graph.