Monte Carlo techniques were used to determine the effect of using common critical values as an approximation for uncommon sample sizes. Results indicate there can be a significant loss in statistical power. Therefore, even though many instructors now rely on computer statistics packages, the recommendation is made to provide more specificity (i.e., values between 30 and 60) in tables of critical values published in textbooks
Many statistical analyses benefit from the assumption that unconditional or conditional distribution...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5. ...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
Monte Carlo techniques were used to determine the effect of using common critical values as an appro...
Nonparametric procedures are often more powerful than classical tests for real world data which are ...
The relationship between reliability and statistical power is considered, and tables that account fo...
A previous study indicated that the Wilcoxon W test showed a power advantage over the student’s t-te...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5. ...
The aim of this article is to show that the T-test can be misleading. We argue that normal or Studen...
Previous research suggests that the power of the independent-samples t test decreases when populatio...
Researchers occasionally have to work with an extremely small sample size, defined herein as N 5...
Statistical significance analysis, based on hypothesis tests, is a common approach for comparing cla...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
Many statistical analyses benefit from the assumption that unconditional or conditional distribution...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5. ...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
Monte Carlo techniques were used to determine the effect of using common critical values as an appro...
Nonparametric procedures are often more powerful than classical tests for real world data which are ...
The relationship between reliability and statistical power is considered, and tables that account fo...
A previous study indicated that the Wilcoxon W test showed a power advantage over the student’s t-te...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5. ...
The aim of this article is to show that the T-test can be misleading. We argue that normal or Studen...
Previous research suggests that the power of the independent-samples t test decreases when populatio...
Researchers occasionally have to work with an extremely small sample size, defined herein as N 5...
Statistical significance analysis, based on hypothesis tests, is a common approach for comparing cla...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
Many statistical analyses benefit from the assumption that unconditional or conditional distribution...
Researchers occasionally have to work with an extremely small sample size, defined herein as N ≤ 5. ...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...