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Is the critical value the same as the p value?

As we know critical value is a point beyond which we reject the null hypothesis. P-value on the other hand is defined as the probability to the right of respective statistic (Z, T or chi). We can use this p-value to reject the hypothesis at 5% significance level since 0.047 < 0.05.

How do you tell if a test statistic is in the critical region?

If the absolute value of the t statistic is larger than the tabulated value, then t is in the critical region. The statistical tests used will be one tailed or two tailed depending on the nature of the null hypothesis and the alternative hypothesis.

What does it mean if the T value is greater than the critical value?

If the absolute value of the t-value is greater than the critical value, you reject the null hypothesis. If the absolute value of the t-value is less than the critical value, you fail to reject the null hypothesis.

How do I find a critical value?

To find the critical value, follow these steps.

  1. Compute alpha (α): α = 1 – (confidence level / 100)
  2. Find the critical probability (p*): p* = 1 – α/2.
  3. To express the critical value as a z-score, find the z-score having a cumulative probability equal to the critical probability (p*).

How do you know if something is sufficient evidence?

If the p-value is less than α, we reject the null hypothesis. If the probability is too small (less than the level of significance), then we believe we have enough statistical evidence to reject the null hypothesis and support the alternative claim.

What do you mean if you fail to reject the null hypothesis?

When we fail to reject the null hypothesis when the null hypothesis is false. The “reality”, or truth, about the null hypothesis is unknown and therefore we do not know if we have made the correct decision or if we committed an error.

Why is the null hypothesis never accepted?

A null hypothesis is not accepted just because it is not rejected. Data not sufficient to show convincingly that a difference between means is not zero do not prove that the difference is zero. If data are consistent with the null hypothesis, they are also consistent with other similar hypotheses.

Can you reject the null and alternative hypothesis?

If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis. You should note that you cannot accept the null hypothesis, but only find evidence against it.