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(6 points) In each part, we have given the significance level and the P-value for a hypothesis test. For each case determine

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P values are the probability that a sample will have an effect at least as extreme as the effect observed in your sample if the null hypothesis is correct.

The p-value indicates how extreme the data are. We compare the p-value with the alpha to determine whether the observed data are statistically significantly different from the null hypothesis:

If the p-value is less than or equal to the alpha (p< .05), then we reject the null hypothesis, and we say the result is statistically significant.
If the p-value is greater than alpha (p > .05), then we fail to reject the null hypothesis, and we say that the result is statistically nonsignificant (n.s.).

1. We are given that

P value = 0.06 and α = 0.07

Thus, we can see that P value < α

Hence in this case we reject the null hypothesis.

2. Hera p value = α = 0.06

Here , p value and alpha (α) both are equal.

Hence , in this case we also reject the null hypothesis.

3. Here, p value = 0.06 and α = 0.01

Now,here we can see that p value > α

Thus , in this case we do not reject the null hypothesis.

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