Difference between statistical and practical significance

What is the difference between statistical significance and practical significance? Why is statistical significance not necessarily of practical important difference to a business decision? Provide an example of this. I need a comment (verify solution) in 25-75 words from the response given below from the question listed above. “Statistical significance refers to the unlikelihood that mean differences observed in the sample have occurred due to sampling error. Practical significance looks at whether the difference is large enough to be of value in a practical sense.” Statistical refers to the null hypothesis where as the practical lays out the calculations and conclusions.

Some reasons why statistical is not of the most importance is because “Tests of statistical significance rarely tell us about the importance of a research result and effect size tells us about magnitude of difference, which is important, but it is difficult for practice-oriented practitioners to comprehend.” If a sample is taken of such few numbers, it will not provide any real evidence towards whether the null hypothesis is really correct or not. There needs to be a greater amount of ‘n’ for the evidence to be practical. The link provided helps at spelling it out more. Still a little confused with this chapter but this may help some of you. Reference:http://dspace.lib.uoguelph.ca/xmlui/bitstream/handle/10214/1869/A_Statistical%20versus%20Practical%20Significance.pdf?sequence=2Statistical significance is not as useful as practical significance in business decisions mainly because statistical information is not freely available and is subject to many tests which mightn’t.

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