“ Statistically significant” refers to values or findings that can be established repetitively if the same method and figures are used again and again (Vaux, 2012). The findings do not occur by probability and hence are true to the specific tests. The values found from tests are usually compared by alpha (0.05) to determine the acceptability of the null hypothesis. Values greater than 0.05 will lead to the rejection of the null hypothesis
Statistics is all about probability and establishing statistically significant values helps organizations plan for the future changes should they happen. For example, if sample tests a statistically significant relationship between aspect A and a fall in sales in a given company, the company may choose to adjust its production so as to prevent losses; if aspect A continues. This is done by inferring the possibility from the results gotten from sampling to the population. This studies help scientists predict and prepare for changes in the ecosystem as a result of altered climate in the future.
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In Biology and health, tests whose findings are found to be statistically significant can be used to conclude about a disease outbreak and thus help in establishing causes of a certain infection in a given place at that particular time. In cases where the problems have been established and the trials have established that certain drugs can be used to treat the given infection significantly, policy makers may recommend use of such drugs to treat the infection in question (Wang et al, 2007). It can also be used in health systems research to determine the utilization of health services by people, establish heath seeking behavior and the quality and affordability of health care services. Such statistics can be used in policy formulation and funding by government institutions and non-governmental organizations so as to help improve health services in areas where health care is found to be scarce or of poor quality (Wang, et al, 2007).
References;
Vaux, D.L. (2012). Research Methods: Know when your numbers are significant. Nature, 492 (7428), 180-181.
Wang, R., et al. (2007). Statistics in medicine-reporting of subgroup analyses in clinical trials. New England Journal of Medicine, 357 (21), 2189-2194.
