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Univariate Statistical Hypothesis Testing  Ungrouped Data 
 
Skewness/Kurtosis (old)  Normality tests for small and large samples.

Skewness/Kurtosis (new)  D'Agostino skewness test, AnscombeGlynn kurtosis test, JarqueBera Normality Test (against normality).

Quasi RandomWalk Identification  Computes the logistic regression probability of a Quasi RandomWalk based on the smallsample Kurtosis pvalue. If the probability is close to 1 then the (financial) time series under investigation is not consistent with the Efficient Market Hypothesis (c.q. RandomWalk).

 
Testing Mean (unknown Variance)  pvalue (old)  computes the 2sided pvalue 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 (unknown Variance)  pvalue (new)  computes the 2sided pvalue 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 twosided hypothesis tests about the mean. In this test it is assumed that the population variance is known.

 
Testing Mean (known Variance)  pvalue  computes the pvalue for one and twosided 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 onesided 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 onesided hypothesis test about the mean, given a userdefined 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 onesided and twosided hypothesis test about the population mean

 
Testing Sample Mean with known Variance  Confidence Interval  computes the confidence intervals for the onesided and twosided 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  pvalue (probability)  computes the pvalue (probability) for the hypothesis test about the variance

 
Testing Variance  Confidence Intervals for Sample Variance  computes the confidence intervals for the onesided and twosided hypothesis test about the sample variance

 
Testing Variance  Confidence Intervals for Population Variance  computes the confidence intervals for the onesided and twosided hypothesis test about the population variance

 
Testing Mean with unknown Variance  Critical Value  computes the 2sided and 1sided 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 twosided hypothesis tests about the population proportion.

 
Testing Population Proportion  PValue  computes the pvalue 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 ttest, unpaired ttest, Welch ttest, and Wilcoxon rank sum test with continuity correction).

Kendall tau Correlation Matrix  Multivariate correlation plot based on Kendall tau rank correlations and their respective pvalues.

Notched Boxplots  Notched Boxplots for a multivariate dataset.

1way ANOVA  Single Factor Analysis of Variance.

2way ANOVA  Two Factor Analysis of Variance.

ChiSquared Tests  This module computes the Pearson ChiSquared test, Exact Pearson ChiSquared by Simulation test, McNemar test, and the Association Plot.
