Explain what "statistical significance" means. Choose the correct explanation below. A. Statistical significance means that the tools used to measure the data introduce error that needs to be accounted for when considering whether or not to reject the null hypothesis. B. Statistical significance means that the sample standard deviation is unusually small, resulting in an unusually large test statistic. C. Statistical significance means that the null hypothesis claims the population proportion is equal to something other than 0.5. D. Statistical significance means that the result observed in a sample is unusual when the null hypothesis is assumed to be true. E. Statistical significance means that the scenario being analyzed will have a meaningful real-world impact.

The statistical significance gives a threshold to measure if a sample result or observed effect is due only to a sampling or it really reflects a characteristics of the population we are studying.

The level of statistical significance is usually 0.05 or 5%, depending on how strong the evidence needs to be and the consequences of the conclusions of the study, taking into account the Type I and Type II errors.

Cricetus Cricetus · Answer 2 · 2021-12-09T08:01:46+01:00

Whenever the null hypothesis has been considered to be accurate, the result obtained in what seems like a collection is uncommon.

The statistical significance provides a cutoff point for determining whether a sampling outcome, as well as observable impact, is attributable mostly to screening whether accurately reflects features of the target population under investigation.
The threshold of such significance is very often 0.05 as well as 5%, on whatever the documentation has to be because the implications of the study's results, recognize the importance of Type I as well as the Type II mistakes.

Thus the response above i.e., "option D" is appropriate.

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