WEEK 3 ASSESSMENT

What is the first step in hypothesis testing?

• a)   Compute the test statistic

• b) Set the significance level

• c) State the hypothesis

• d) Make a decision

2.  In hypothesis testing, what is the purpose of the null hypothesis (H₀)?

• a)   It states the conclusion of the test

• b)   It is the claim that we want to prove

• c) It represents no effect or no difference

• d) It determines the test statistic

3.  Why is the significance level (α) important in hypothesis testing?

• a)   It helps determine the sample size

• b)   It sets the threshold for rejecting H₀

• c)  It ensures the alternative hypothesis is correct

• d)   It directly affects the population mean

4.  When do we reject the null hypothesis?

• a)   When the test statistic is greater than the critical value

• b)   When the test statistic is within the acceptance region

• c)  When the p-value is greater than α

• d)   When the test statistic falls in the rejection region

5.  Why is hypothesis testing useful in real-life decision-making?

• a) It helps make conclusions based on emotions

• b)   It allows decisions to be based on statistical evidence

• c)  It eliminates uncertainty completely

• d)   It only applies to scientific research.

6. Which of the following is the correct sequence of hypothesis testing?

• a)   Compute test statistic → Set significance level → State hypotheses → Decision → Conclusion

• b)     State hypotheses → Determine the test to be use→ Compute test statistic → Decision → Make a conclusion

• c)   Set significance level → Compute test statistic → Decision → State hypotheses → Conclusion

• d)   State hypotheses → Compute test statistic → Determine critical value → Conclusion

7.  What does rejecting the null hypothesis mean?

• a)   There is sufficient evidence to support the alternative hypothesis

• b)   The sample size is too small

• c)  The null hypothesis is always incorrect

• d)   The test was inconclusive

8.  What type of error occurs when we reject a true null hypothesis?

• a)   Type I error

• b)   Type II error

• c)  Sampling error

• d)   Statistical bias

9.     If the significance level is 0.05, what does it mean?

• a) There is a 5% probability of rejecting a true null hypothesis

• b) The null hypothesis is true 5% of the time

• c)  There is a 5% chance of accepting the alternative hypothesis

• d)   The test statistic will always be greater than the critical value

10.       Why is hypothesis testing important in decision-making?

• a)   It eliminates uncertainty in all decisions

• b)   It provides a structured approach to making conclusions based on data

• c)  It always confirms the researcher's beliefs

• d)   It only applies to academic research