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2. Free statistical software - Wikipedia

   en.wikipedia.org/wiki/Free_statistical_software

   There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures.

3. G*Power - Wikipedia

   en.wikipedia.org/wiki/G*Power

   G*Power is a free-to use software used to calculate statistical power. The program offers the ability to calculate power for a wide variety of statistical tests including t-tests , F-tests , and chi-square-tests , among others.

4. PASS Sample Size Software - Wikipedia

   en.wikipedia.org/wiki/PASS_Sample_Size_Software

   PASS is a computer program for estimating sample size or determining the power of a statistical test or confidence interval. NCSS LLC is the company that produces PASS. NCSS LLC also produces NCSS (for statistical analysis). PASS includes over 920 documented sample size and power procedures.

5. PS Power and Sample Size - Wikipedia

   en.wikipedia.org/wiki/PS_Power_and_Sample_Size

   The program provides methods that are appropriate for matched and independent t-tests, [2] survival analysis, [5] matched [6] and unmatched [7] [8] studies of dichotomous events, the Mantel-Haenszel test, [9] and linear regression. [3] The program can generate graphs of the relationships between power, sample size and the detectable alternative ...

6. List of statistical software - Wikipedia

   en.wikipedia.org/wiki/List_of_statistical_software

   nQuery Sample Size Software – Sample Size and Power Analysis Software [5] O-Matrix – programming language; OriginPro – statistics and graphing, programming access to NAG library; PASS Sample Size Software (PASS) – power and sample size software from NCSS

7. Power (statistics) - Wikipedia

   en.wikipedia.org/wiki/Power_(statistics)

   In addition, the concept of power is used to make comparisons between different statistical testing procedures: for example, between a parametric test and a nonparametric test of the same hypothesis. Tests may have the same size , and hence the same false positive rates, but different ability to detect true effects.