The Y Fits data table contains a row for Y variable. For each Y, the columns in the table summarize information about the model fit. If you select the Robust Fit option on the launch window, the models are fit using Huber M-estimation.
Y
The specified response columns.
RSquare
The multiple correlation coefficient.
RMSE
The Root Mean Square Error.
Count
The number of observations (or sum of the Weight variable).
Overall FRatio
The test statistic for model fit from the Analysis of Variance report in Least Squares Fit.
Overall PValue
The p-value for the overall test of model significance.
Overall LogWorth
The LogWorth of the p-value for the overall test of model significance.
Overall FDR PValue
The overall p-value adjusted for the false discovery rate. (See The Response Screening Report.)
Overall FDR LogWorth
The LogWorth of the Overall FDR PValue.
Overall Rank Fraction
The rank of the Overall FDR LogWorth expressed as a fraction of the number of tests. If the number of tests is m, the largest Overall FDR LogWorth value has Rank Fraction 1/m, and the smallest has Rank Fraction 1.
<Effect> PValue
These columns contain p-values for tests of each model effect. These columns are arranged in a group called PValue in the columns panel.
<Effect> LogWorth
These columns contain LogWorths for the p-values for tests of each model effect. These columns are arranged in a group called LogWorth in the columns panel.
<Effect> FDR LogWorth
These columns contain FDR LogWorths for tests of each model effect. These columns are arranged in a group called FDR LogWorth in the columns panel.
The Y Fits data table also contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable, JMP creates a Y Fits table for each level of the By variable, and the Original Data variable gives the By variable and its level.