Statistically Significant Results
One of the most important aspects of research findings is to ensure that the results are significant or meaningful in order to influence an appropriate course of action. In this case, the significance of the findings of a study can be described as the quality of being important. Therefore, the efforts carried out by a researcher or group of researchers should be geared towards ensuring the process generates important findings. However, there have been numerous concerns regarding the statistical significance and/or practical significance of the findings of a study. These concerns are attributed to the fact that the findings of a study can be statistically significant but not meaningful.
Statistically significant findings of a study basically predict the probability that a relationship observed in the data was a by-product of chance and the likelihood that the variables are actually unrelated. In this case, the research tests attempt to generate evidence that a null hypothesis can be rejected. Consequently, there is likelihood for finding a difference between groups even in the absence of such difference or concluding that a difference does not exist when it actually does. Generally, statistically significant findings demonstrate a benchmark that is easily understood...
This implies that these findings provide important information regarding a research project that is comparable to the findings of other studies.
Research findings may be statistically significant but not meaningful since they can show precise numbers but without any relationship with or link to practical significance ("Tests for Significance" par, 76) These findings are not meaningful since they only provide precise numbers but do not demonstrate whether the study has been properly developed and executed. Research findings may be significant in providing precise numbers regarding the study or research process but not meaningful because of failure to show the practicality of the findings.
An example of how research findings can be statistically significant but not meaningful is in the medical field. The findings of a research in the medical field can be clinically significant but not clinically important. For instance, when examining the difference between new and old therapy, the findings can be statistically significant but not meaningful. In this case, the issue under evaluation is whether the difference identified in the research is large enough to cause changes in practice. If a small improvement in the new therapy is identified, it may not be adequate enough…
Statistical Significance and Meaningfulness Scenario Critically evaluate the sample size To begin with, sample size is very significant. In this particular scenario, the sample size is much more 30, and therefore considered to be a large sample size. Owing to the large sample size, it is expected that the sampling error will be small. And, a small sampling error results in a significant test, in most cases. This is similar to the results
Meaningfulness refers to the practical, real world application of a statistic. If a statistically significant correlation between variables, for instance, has meaningfulness that correlation says something to the real world and understanding that correlation can have an impact on how people adjust to the situation from here on out. Therefore, while statistical significance is helpful, it is not the end-all-be-all for research: a research finding has to be meaningful
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