The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected is said to be
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The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected is said to be
Critical Value.
Critical value is an important part in the hypothesis testing, which helps decide whether to null the hypothesis or not. Hypothesis testing is a form of data analysis. It can be assessed by the observation of process that is modeled via a set of random variables.
The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected is said to be
Critical Value.
Critical value is an important part in the hypothesis testing, which helps decide whether to null the hypothesis or not. Hypothesis testing is a form of data analysis. It can be assessed by the observation of process that is modeled via a set of random variables.
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"The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected is said to be Critical value.
The idea behind the critical value is we must choose a false rejection rate which is called as significance level . Mostly used significance value is 5%.
If the value falls down below the critical value the "null hypothesis" is rejected and if the value goes above the critical value the "null hypothesis" is not rejected and further steps are initiated."
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