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All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

Free Software for Statistical Hypothesis Tests (Calculators):

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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, Anscombe-Glynn kurtosis test, Jarque-Bera Normality Test (against normality).
Quasi Random-Walk IdentificationComputes the logistic regression probability of a Quasi Random-Walk based on the small-sample Kurtosis p-value. If the probability is close to 1 then the (financial) time series under investigation is not consistent with the Efficient Market Hypothesis (c.q. Random-Walk).
Testing Mean (unknown Variance) - p-value (old)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 (unknown Variance) - p-value (new)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 Valuecomputes 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-valuecomputes 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 Errorcomputes 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 sizecomputes 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 Intervalcomputes the confidence intervals for the one-sided and two-sided hypothesis test about the population mean
Testing Sample Mean with known Variance - Confidence Intervalcomputes 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 Variancecomputes the confidence intervals for the one-sided and two-sided hypothesis test about the sample variance
Testing Variance - Confidence Intervals for Population Variancecomputes the confidence intervals for the one-sided and two-sided hypothesis test about the population variance
Testing Mean with unknown Variance - Critical Valuecomputes 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 Valuecomputes the critical values for one- and two-sided hypothesis tests about the population proportion.
Testing Population Proportion - P-Valuecomputes the p-value of the population proportion test.

Bivariate and Multivariate Statistical Hypothesis Testing - Ungrouped Data
Two Sample Tests about the MeanPaired 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 MatrixMultivariate correlation plot based on Kendall tau rank correlations and their respective p-values.
Notched BoxplotsNotched Boxplots for a multivariate dataset.
1-way ANOVASingle Factor Analysis of Variance.
2-way ANOVATwo Factor Analysis of Variance.
Chi-Squared TestsThis module computes the Pearson Chi-Squared test, Exact Pearson Chi-Squared by Simulation test, McNemar test, and the Association Plot.





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To cite Wessa.net in publications use:
Wessa, P. (2014), Free Statistics Software, Office for Research Development and Education,
version 1.1.23-r7, URL http://www.wessa.net/

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Software Version : 1.1.23-r7
Algorithms & Software : Patrick Wessa, PhD
Server : www.wessa.net

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