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Two different ways that research uses hypothesis testing is one-tail and two-tail testing. One-tail test is for determining the difference in specific direction. Two-tailed test has no direction to show the difference either positive or negative direction. When there is no effect on the population which is shown by evidence the null is rejected. With accurate results the decision is made to reject the null. Type I and Type II of errors are related to decision to whether or not to reject null. Type I is whether population from independent variable has not effect then null is rejected when it is true. Type II is no effect on population from independent variable is effects then null failed and is rejected in error. Hypothesis testing is scientific research to improve patient care. Leadership focus is on improving quality of care.
Example of how research uses hypothesis testing is in diabetic patient treated with compound which will lower concentration of HbA1c in 24 week treatment. Some patients had compound and other had placebo. Mean value is 1% lower than patient taking placebo. P value range is 0 (unlikely) and 1 (certain). The smaller the P value, the more unsustainable is the null hypothesis. When the null hypothesis is untenable, we can reject it and adopt the alternative hypothesis (Schindler, 2015).
Another example, is on a smoking pregnant mother had 10 or more cigarettes and child IQ. The children are ages 1, 2, 3 or 4 years of age. Mean IQ score for children is the same for both mothers that smoked and mothers that did not smoke. This is a null hypothesis. Smoking mothers is not the same as mother that does not smoke. This is alternate hypothesis. Children born to women who smoked 10+ cigarettes per day during pregnancy had developmental quotients at 12 and 24 months of age that were 6.97 points lower (averaged across these two time points) than children born to women who did not smoke during pregnancy (95% CI: 1.62,12.31, P = .01); at 36 and 48 months they were 9.44 points lower (95% CI: 4.52, 14.35, P = .0002)(Olds et al., 1994, p. 223). Two tailed test for possibility that the mean IQ score will be higher for smoking mother’s. P value is statistically significant difference.
Reference:
Grand Canyon University (Ed). (2018). Applied statistics for health care. Retrieved from
https://lc.gcumedia.com/hlt362v/applied-statistics…
Hypothesis testing-Examples and Case Studies. (n.d.). Retrieved from
https://www2.stat.duke.edu/courses/Fall11/sta10/STA10lecture21.pdf
Schindler, T. M. (2015). Hypothesis Testing in Clinical Trials. AMWA Journal: American
Medical Writers Association Journal, 30(2), 78–80. Retrieved from https://search-ebscohost-
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