Pairs of P-values and significance levels, α, are given. For each pair, state whether the observed P-value would lead to rejection of H0 at the given significance level. (a) P-value = 0.074, α = 0.05 reject H0 do not reject H0 (b) P-value = 0.006, α = 0.001 reject H0 do not reject H0 (c) P-value = 0.494, α = 0.05 reject H0 do not reject H0 (d) P-value = 0.074, α = 0.10 reject H0 do not reject H0 (e) P-value = 0.028, α = 0.01 reject H0 do not reject H0 (f) P-value = 0.296, α = 0.10 reject H0 do not reject H0

(a) P-value = 0.074, α = 0.05 do not reject H0

(b) P-value = 0.006, α = 0.001 do not reject H0

(c) P-value = 0.494, α = 0.05 do not reject H0

(d) P-value = 0.074, α = 0.10 reject H0

(e) P-value = 0.028, α = 0.01 do not reject H0

(f) P-value = 0.296, α = 0.10 do not reject H0

Step-by-step explanation:

The p-value is used to determine the statistical significance of the results of a statistical test. The p-value is the probability that the null hypothesis is correct. Smaller the p-value, higher is the probability that the alternate hypothesis is correct. On the other hand, the significance level (α) is the probability of rejecting the null hypothesis when it is true. It is the risk that you are willing to take in saying that there are differences between groups when there are not.

In order to reject the null hypothesis, the p-value should be lower than the significance level (α).