The development of SigmaStat was discontinued in 2007 in favor of integrating all of SigmaStat's functions and features into SigmaPlot starting at version 11. When that occurred, it was also time to update the features and functions that were in prior versions of SigmaStat. Below are some of the many improvements to our statistical analysis functions now in SigmaPlot:

• Cox Regression - This includes the proportional hazards model with stratification to study the impact of potential risk factors on the survival time of a population. The input data can be categorical.
• One-Sample T-test - Tests the hypothesis that the mean of a population equals a specified value.
• Odds Ratio and Relative Risk tests - Both tests the hypothesis that a treatment has no effect on the rate of occurrence of some specified event in a population. Odds Ratio is used in retrospective studies to determine the treatment effect after the event has been observed. Relative Risk is used in prospective studies where the treatment and control groups have been chosen before the event occurs.
• Shapiro-Wilk Normality test - A more accurate test than Kolmogorov-Smirnov for assessing the normality of sampled data. Used in assumption checking for many statistical tests, but can also be used directly on worksheet data.
• New Result Graph - ANOVA Profile Plots: Used to analyze the main effects and higher-order interactions of factors in a multi-factor ANOVA design by comparing averages of the least square means.
• New Probability Transforms - Twenty-Four new functions have been added to SigmaStat´s Transform language for calculating probabilities and scores associated with distributions that arise in many fields of study.
• New Interface Change - Nonlinear Regression: An easy to use wizard interface and more detailed reports.
• New Interface Change - Quick Transforms: An easier way of performing computations in the worksheet.
• New Interface Change - New User Interface: Allows the user to work more easily with Excel worksheets.
• Yates correction added to the Mann-Whitney test - Yates correction for continuity, or Yates chi-square test is used when testing for independence in a contingency table when assessing whether two samples of observations come from the same distribution.
• Improved Error Messaging - Improved error messages have added information when assumption checking for ANOVA has failed.