The Analyse-it Standard Edition version 3.00 is now available, see Analyse-it Standard Edition to purchase a licence or download a trial.
We’re pleased to release the final beta of the Analyse-it Standard Edition, v3.0. The beta is now publicly open to anyone as we iron out any final issues and conduct final testing before release.
To download the beta, please visit:
Screenshot: Analyse-it fit model analysis includes an influence plot to identify points with a substantial effect on the fitted model.
Many of you have asked what statistical tests and plots are included in the new release. The full specification is shown below. In coming weeks we'll announce pricing, upgrade pricing, and award free licences to the beta testers who contributed most time and effort.
Mean, Median, Variance, SD, Skewness, Kurtosis
Quantiles / Percentiles
Frequency distribution table
Correlation coefficients – r, rs, tau
Mean error bar plot
Normal Q-Q plot
Scatter plot matrix
Outlier and influence plot
Grouped frequency plot
Stacked frequency plot
Pie frequency plot
Likelihood ratio G2
t-based confidence interval for mean
Z-based confidence interval for mean
Thompson-Savur confidence interval for median
Tukey confidence interval for Hodges-Lehmann pseudo-median
t-based confidence interval for mean difference
Z-based confidence interval for mean difference
Welch-Satterthwaite t-based confidence interval for mean difference
Hodges-Lehmann location shift
Tukey confidence interval for Hodges-Lehmann location shift
Tukey-Kramer confidence interval for mean difference
Dunnett confidence interval for mean difference
X2-based confidence interval for variance
F-based confidence interval for variance ratio
Clopper-Pearson exact confidence interval for proportion / odds
Wilson score confidence interval for proportion / odds
Proportion difference (risk difference)
Proportion ratio (risk ratio)
Miettinen-Nurminen score confidence interval for proportion difference / proportion ratio / odds-ratio
Newcombe score confidence interval for proportion difference
Conditional exact confidence interval for odds ratio
Fisher Z confidence interval for Pearson r
Samara-Randles confidence interval for Kendall tau
Regression and model fitting
Polynomial 2nd to 6th order
Multiple linear regression
Binary logistic regression
Advanced multiple linear and logistic regression models with simple, crossed, polynomial and factorial terms, with categorical explanatory variables coded as dummy variables
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