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| Univariate Statistical Hypothesis Testing - Ungrouped Data | |
| Skewness/Kurtosis Test | D'Agostino skewness test, Anscombe-Glynn kurtosis test, Jarque-Bera Normality Test (against normality). |
| Skewness-Kurtosis Plot | Skewness-Kurtosis plot as proposed by Cullen and Frey (1999). |
| Testing Mean (unknown Variance) - p-value | computes the 2-sided p-value for the statistical hypothesis test about the mean when the population variance is unknown. This test can be applied to any univariate dataset. |
| Testing Mean (known Variance) - Critical Value | computes the critical value for one- and two-sided hypothesis tests about the mean. In this test it is assumed that the population variance is known. |
| Testing Mean (known Variance) - p-value | computes the p-value for one- and two-sided hypothesis tests about the mean. In this test it is assumed that the population variance is known. |
| Testing Mean (known Variance) - Type II Error | computes the Type II Error for the one-sided hypothesis test about the mean. In this test it is assumed that the population variance is known. |
| Testing Mean (known Variance) - sample size | computes the sample size for the one-sided hypothesis test about the mean, given a user-defined type I and II error. In this test it is assumed that the population variance is known. |
| Testing Population Mean with known Variance - Confidence Interval | computes the confidence intervals for the one-sided and two-sided hypothesis test about the population mean |
| Testing Sample Mean with known Variance - Confidence Interval | computes the confidence intervals for the one-sided and two-sided hypothesis test about the sample mean |
| Testing Variance - Critical Value (Region) | computes the critical value (region) for the hypothesis test about the variance |
| Testing Variance - p-value (probability) | computes the p-value (probability) for the hypothesis test about the variance |
| Testing Variance - Confidence Intervals for Sample Variance | computes the confidence intervals for the one-sided and two-sided hypothesis test about the sample variance |
| Testing Variance - Confidence Intervals for Population Variance | computes the confidence intervals for the one-sided and two-sided hypothesis test about the population variance |
| Testing Mean with unknown Variance - Critical Value | computes the 2-sided and 1-sided confidence intervals for the statistical hypothesis test about the mean when the population variance is unknown. This test can be applied to any univariate dataset. |
| Testing Population Proportion - Critical Value | computes the critical values for one- and two-sided hypothesis tests about the population proportion. |
| Testing Population Proportion - P-Value | computes the p-value of the population proportion test. |
| Bivariate and Multivariate Statistical Hypothesis Testing - Ungrouped Data | |
| Two Sample Tests about the Mean | Paired and Unpaired Two Sample Tests about the Mean (paired t-test, unpaired t-test, Welch t-test, and Wilcoxon rank sum test with continuity correction). |
| Kendall tau Correlation Matrix | Multivariate correlation plot based on Kendall tau rank correlations and their respective p-values. |
| Notched Boxplots | Notched Boxplots for a multivariate dataset. |
| 1-way ANOVA | Single Factor Analysis of Variance. |
| 2-way ANOVA | Two Factor Analysis of Variance. |
| Chi-Squared Tests | This module computes the Pearson Chi-Squared test, Exact Pearson Chi-Squared by Simulation test, McNemar test, and the Association Plot. |
| Compare Correlations | This module tests the difference between two Pearson Correlations. |