Tutorials in clinical research: VII. Understanding comparative statistics (contrast)--part B: application of T-test, Mann-Whitney U, and chi-square.
OBJECTIVE
This tutorial on comparative statistics has been written in two complementary segments. The first paper (part A) focused on explaining the general concepts of the null hypothesis and statistical significance. This second article (part B) addresses the application of three specific statistical tests. These two articles should be read sequentially and the first article should be available for reference while one reads the second.


METHODS
Tutorial.


METHODS
The authors met weekly for 10 months to discuss clinical research articles and the applied statistics. The difficulty was not the material but the effort to make it easy to read and as short as possible.


RESULTS
The article discusses the application of three common statistical indexes of contrast, chi2, Mann-Whitney U, and Student t-test and other concepts, such as sample size, degrees of freedom, errors, power, and confidence intervals.


CONCLUSIONS
Statistical tests generate a number known as a statistic (chi2, U, t), which is sometimes called a "critical ratio" because it helps us to make a decision. This number is then associated with a probability, or P value. Sample size is a crucial element in the initial design of a research project and in the subsequent ability of the results to show statistical significance if the difference is clinically important. The example data used in this paper demonstrate the application of the three specific tests and illustrate the effect of sample size on the results.
Neely
J Gail
JG
Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, 660 South Euclid Avenue, Box 8115, St. Louis, MO 63110, USA. jgneely@aol.com
Hartman
James M
JM
Forsen
James W
JW
Wallace
Mark S
MS
D035843:Biomedical Research; D016009:Chi-Square Distribution; D003627:Data Interpretation, Statistical; D006801:Humans; D012107:Research Design; D018401:Sample Size; D018709:Statistics, Nonparametric