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Sigma Plot Statistics
Sigma Plot 11 now includes the capabilities of Sigma Stat
Major test
Minor tests
- Odds Ratio Statistic
- Relative Risk Statistic
- One Sample t-test
- Shapiro-Wilk Normality Test
New Result Graphs
- Anova Profile Plots
- Cox Regression Plots (Cumulative Hazard, Log Log Survival)
24 New Probability Transforms
- Gamma, Weibull, Cauchy, Error, LogNormal, Exponential, Logistic, LogLogistic
More informative Anova messages
Regression Wizard
- Linear and nonlinear regressions
- Over 100 built-in, graphically-illustrated equations
- Marquardt-Levenberg algorithm with up to 10 independent variables and 25 parameters
- Define constraints, tolerance, step size and iterations
- Automatically determines your initial parameters
- Writes a complete statistical report to your SigmaPlot Notebook
- Automatically graphs your results on new or existing graphs
- Edit code so you can customize the SigmaPlot library of functions or create your own
- Specify the range for the predicted values output by curve-fitter
- Automatic Linear Regressions
- Up to 10th order with confidence and prediction intervals and regression statistics
- Column Statistics Generated Automatically
- Size, sum, mean, minimum, maximum, standard deviation, standard error, skewness, minimum positive, number of missing values, and 95% & 99% confidence intervals
Automatic Linear Regressions
- Up to 10th order with confidence and prediction intervals and regression statistics
Column Statistics Generated Automatically
- Size, sum, mean, minimum, maximum, standard deviation, standard error, skewness, minimum positive, number of missing values, and 95% & 99% confidence intervals
Dynamic Curve Fitting
- Converged - Those fitsfthat satisfied the convergence criterion.
- Singular Solutions - Those convergent fitsfwhose covariance matrix is singular.
- Ill-Conditioned Solutions - Those convergent fits whose covariance matrix is ill-conditioned (to machine precision).
- Evaluation Failures - Fits that failed to converge due to an evaluation error of the fit equation induced by certain (out of domain) parameter values.
- Iterations Exceeding - Fits that failed to converge after the iteration limit was reached. This user specified limit is inserted into the brackets above.
- Inner-Loop Failures - Fits where the Levenberg-Marquardt parameter has increased above a prescribed value when searching for a parameter direction to decrease the residual sum of squares.
Global Curve Fitting
- Converged - Those fits that satisfied the convergence criterion.
- Singular Solutions - Those convergent fits whose covariance matrix is singular.
- Ill-Conditioned Solutions - Those convergent ffits whose covariance matrix is ill-conditioned (to machine precision).
- Evaluation Failures - Fits that failed to converge due to an evaluation error of the fit equation induced by certain (out of domain) parameter values.
- Iterations Exceeding - Fits that failed to converge after the iteration limit was reached. This user specified limit is inserted into the brackets above.
- Inner-Loop Failures - Fits where the Levenberg-Marquardt parameter has increased above a prescribed value when searching for a parameter direction to decrease the residual sum of squares.
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