Posted by **big1ne** at Jan. 17, 2012

A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power. As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb." PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.

Posted by **Artist14** at Jan. 7, 2012

A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power. As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb." PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.

Posted by **big1ne** at Aug. 31, 2011

A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power. As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb." PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.

Posted by **Dizel_** at June 2, 2011

Since 1981, NCSS has specialized in providing statistical analysis software to researchers, businesses, and academic institutions. Our current release, NCSS 2007, is comprehensive, easy to use, and runs under Windows Vista, XP, 2000, NT, ME, 98, and 95.

Posted by **Artist14** at Feb. 10, 2011

A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power. As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb." PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.

Posted by **Artist14** at Dec. 23, 2010

A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power.

As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb."

PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.

Posted by **Dizel_** at Aug. 26, 2010

PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough. PASS lets you solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal. PASS is a standalone system. Although it is integrated with NCSS, you do not have to own NCSS to run it. You can use it with any statistical software you want. PASS 2008 runs under Windows Vista, XP, 2000, NT, ME, 98, and 95.

Posted by **bityan** at Nov. 6, 2009

PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough. PASS lets you solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal.

Posted by **bityan** at Sept. 16, 2009

PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough. PASS lets you solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal.

Posted by **lockedtwice** at Jan. 11, 2009

NCSS : Since 1981, NCSS has specialized in providing statistical analysis software to researchers, businesses, and academic institutions. Our current release, NCSS 2007, is comprehensive, easy to use, and runs under Windows Vista, XP, 2000, NT, ME, 98, and 95.

GESS : GESS makes statistical analysis of microarray gene expression data fast and easy. With this well-documented package, you will not have to worry about complex programming or confusing statistical output. Because this software was developed by a company with over 20 years of experience creating commercial statistical software, you will be confident with your results.