To determine the result of the hypothesis test, we compare the p-value to the significance level ($\alpha$).

• Given:
  • Test statistic = 2.23
  • p-value = 0.0339
  • $\alpha = 0.01$

Decision Rule:

• If the p-value is less than $\alpha$, reject the null hypothesis ($H_0$).
• If the p-value is greater than or equal to $\alpha$, do not reject the null hypothesis ($H_0$).

Comparison:

• p-value (0.0339) is greater than $\alpha$ (0.01).

Conclusion:

• Since the p-value is not less than $\alpha$, we do not reject the null hypothesis ($H_0$).

So, the correct answer is:

Do not reject Ho since p-value is not less than α.

Would you like more details or have any questions?

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Here are 5 related questions you might find useful:

1. What does it mean to reject the null hypothesis?
2. How do you interpret the p-value in hypothesis testing?
3. What are Type I and Type II errors in hypothesis testing?
4. How is the significance level ($\alpha$) chosen in a hypothesis test?
5. What are the implications of not rejecting the null hypothesis?

Tip: Always compare the p-value with the significance level ($\alpha$) to make the correct decision in hypothesis testing.