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- Paired or unpaired t-test. Reports the P-value and the confidence interval.
- Automatically generates volcano graphs (differences from P values) from multiple t-test analyzes.
- Nonparametric Mann-Whitney test, including confidence intervals for differences in medians.
- Kolmogorov-Smirnov test to compare two groups.
- Wilcoxon test with median confidence intervals.
- Perform multiple t-tests at once, using the false discovery rate (or Bonferroni’s multiple comparisons) to choose which ratio is a discovery for further study.
- The usual or repeated ANOVA measurements are followed by the Tukey, Newman-Keuls, Dunnett, Bonferroni, or Holm-Sidak double comparison test, the trend post-test, or the Fisher’s Least Significant test.
- One-way ANOVA without assuming that the population with the same standard deviation uses Brown-Forsythe and Welch ANOVA, followed by an appropriate comparison test (Games-Howell, Tamhane T2, Dunnett T3)
- Many multiple comparison tests were accompanied by confidence intervals and P values adjusted for variability.
- Greenhouse-Geisser correction so that repeated measurements of one, two, and three-factor ANOVA do not necessarily assume roundness. If this option is selected, the multiple comparison test does not assume roundness either.
- Kruskal-Wallis or Friedman unidirectional nonparametric ANOVA with Dunn’s post-test.
- Fisher’s exact test or chi-square test. Calculate the relative risk and the ratio of opportunities with confidence intervals.
- Two-way ANOVA, even with missing values with multiple post-tests.
- Bidirectional ANOVA, with repeated measurements on one or both factors. The multiple LSD comparisons of Tukey, Newman-Keuls, Dunnett, Bonferroni, Holm-Sidak, or Fisher tested the main and simple effects.
- Three-way ANOVA (limited to two levels in two factors and several levels in the third).
- Analysis of repeated measurement data (one, two, and three directions) using a mixed-effects model (similar to repeated measures ANOVA, but capable of handling missing data).
- Kaplan-Meier survival analysis. Compare the curves with log-rank tests (including trend tests).
- Compare data from nested data tables using a nested t-test or a one-way nested ANOVA (using a mixed-effects model).
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- New kinds of statistical analyses
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- Microsoft Windows Vista, 7, 8 or 10, 32/64-bit.
- Macintosh 10.7 or higher.
- Screen Resolution at least 800 x 540 pixels.
- Hard disk space is about 100 MB.
- 1GB RAM is required.
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