Statistical significance refers to the claim that a result from data generated by testing or experimentation is not likely to occur randomly or by chance but is instead likely to be attributable to a specific cause. Having statistical significance is important for academic disciplines or practitioners that rely heavily on analyzing data and research, such as economics, finance , investing , medicine , physics, and biology. Statistical significance can be considered strong or weak. When analyzing a data set and doing the necessary tests to discern whether one or more variables have an effect on an outcome, strong statistical significance helps support the fact that the results are real and not caused by luck or chance. Simply stated, if a p-value is small then the result is considered more reliable. Problems arise in tests of statistical significance because researchers are usually working with samples of larger populations and not the populations themselves.
Statistics and Probability
Statistics Help - Free Math Help
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