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What does it mean for a hypothesis test to be statistically significant? How is this different...

What does it mean for a hypothesis test to be statistically significant? How is this different from our everyday notions of “significant”
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A hypothesis test is said to be statistically  significant  when the p-estimation of the test is less than the level of significance. Fundamentally, a measurably huge outcome is a result which isn't credited to chance. At the end of the day, if the null hypothesis  of the test is valid, there is a low likelihood that the outright estimation of test-measurement will be not as much as that of obtained estimation of test-measurement.

This is not the same as our practical  thought of significance as statistical significance doesn't imply practical significance. The test utilized for factual importance depends upon the decision of level of significance. A test can be significant measurably at 5% level of criticalness if the p-esteem is 0.04, anyway it won't be noteworthy at 1% level of significance. Functional importance depends more upon individual judgment.

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