BUS5112 Quantitative Research Methods Unit 6 Graded Quiz — 25
Q&A Verified Answers 2025
Course:
BUS5112 Quantitative Research Methods — University of the People (UoPeople)
Level:
MBA
Year:
2025/2026
Format:
Graded Quiz Solutions — 25 Q&A with Verified Answers
BUS5112 Unit 6 Graded Quiz — Hypothesis Testing and Inferential
Statistics
25 Questions with Verified Answers | Score: 96/100
Question 1:
In hypothesis testing, which of the following statements best describes the null hypothesis
($H_0$)?
A) It represents the claim or theory that the researcher is trying to prove is true.
B) It asserts that the sample mean is exactly equal to the population standard deviation.
C) It is a statement indicating no effect, no difference, or no relationship between variables.
D) It establishes the margin of error acceptable within the statistical model.
Answer: C
Explanation:
The null hypothesis always represents the "status quo" or an assumption of no difference, no
effect, or no relationship between the variables being studied. Option A describes the alternative
hypothesis. Options B and D are nonsensical statements regarding hypothesis definitions.
Question 2:
, A marketing manager believes that a new advertising campaign will increase average daily sales
beyond the current $10,000. How should the alternative hypothesis ($H_a$) be formulated?
A) $H_a$: $\mu < \$10,000$
B) $H_a$: $\mu \le \$10,000$
C) $H_a$: $\mu = \$10,000$
D) $H_a$: $\mu > \$10,000$
Answer: D
Explanation:
The alternative hypothesis represents the researcher's specific claim or what they are attempting
to demonstrate. Since the manager believes sales will increase beyond $10,000, the alternative
hypothesis is that the population mean ($\mu$) is strictly greater than $10,000. Options B and C
describe potential null hypotheses, and A represents a decrease.
Question 3:
Which of the following scenarios best illustrates a Type I error in statistical decision making?
A) Failing to recognize that a manufacturing process is producing defective parts when it actually
is.
B) Concluding that a new drug is effective when it actually has no effect.
C) Correctly identifying that a new training program improves employee productivity.
D) Retaining the null hypothesis when it is, in fact, true in reality.
Answer: B
Explanation:
A Type I error (false positive) occurs when a researcher incorrectly rejects a true null hypothesis.
In Option B, the researcher incorrectly concludes the drug works (rejecting $H_0$ of no effect)
when it actually doesn't. Option A describes a Type II error (false negative). Options C and D
describe correct decisions.
Question 4:
A quality control analyst wants to minimize the risk of accidentally shutting down a properly
functioning production line based on a false alarm. To achieve this, what statistical adjustment
should the analyst make?
A) Decrease the significance level ($\alpha$) from 0.05 to 0.01.
B) Increase the significance level ($\alpha$) from 0.05 to 0.10.
C) Decrease the sample size used for quality testing.
Q&A Verified Answers 2025
Course:
BUS5112 Quantitative Research Methods — University of the People (UoPeople)
Level:
MBA
Year:
2025/2026
Format:
Graded Quiz Solutions — 25 Q&A with Verified Answers
BUS5112 Unit 6 Graded Quiz — Hypothesis Testing and Inferential
Statistics
25 Questions with Verified Answers | Score: 96/100
Question 1:
In hypothesis testing, which of the following statements best describes the null hypothesis
($H_0$)?
A) It represents the claim or theory that the researcher is trying to prove is true.
B) It asserts that the sample mean is exactly equal to the population standard deviation.
C) It is a statement indicating no effect, no difference, or no relationship between variables.
D) It establishes the margin of error acceptable within the statistical model.
Answer: C
Explanation:
The null hypothesis always represents the "status quo" or an assumption of no difference, no
effect, or no relationship between the variables being studied. Option A describes the alternative
hypothesis. Options B and D are nonsensical statements regarding hypothesis definitions.
Question 2:
, A marketing manager believes that a new advertising campaign will increase average daily sales
beyond the current $10,000. How should the alternative hypothesis ($H_a$) be formulated?
A) $H_a$: $\mu < \$10,000$
B) $H_a$: $\mu \le \$10,000$
C) $H_a$: $\mu = \$10,000$
D) $H_a$: $\mu > \$10,000$
Answer: D
Explanation:
The alternative hypothesis represents the researcher's specific claim or what they are attempting
to demonstrate. Since the manager believes sales will increase beyond $10,000, the alternative
hypothesis is that the population mean ($\mu$) is strictly greater than $10,000. Options B and C
describe potential null hypotheses, and A represents a decrease.
Question 3:
Which of the following scenarios best illustrates a Type I error in statistical decision making?
A) Failing to recognize that a manufacturing process is producing defective parts when it actually
is.
B) Concluding that a new drug is effective when it actually has no effect.
C) Correctly identifying that a new training program improves employee productivity.
D) Retaining the null hypothesis when it is, in fact, true in reality.
Answer: B
Explanation:
A Type I error (false positive) occurs when a researcher incorrectly rejects a true null hypothesis.
In Option B, the researcher incorrectly concludes the drug works (rejecting $H_0$ of no effect)
when it actually doesn't. Option A describes a Type II error (false negative). Options C and D
describe correct decisions.
Question 4:
A quality control analyst wants to minimize the risk of accidentally shutting down a properly
functioning production line based on a false alarm. To achieve this, what statistical adjustment
should the analyst make?
A) Decrease the significance level ($\alpha$) from 0.05 to 0.01.
B) Increase the significance level ($\alpha$) from 0.05 to 0.10.
C) Decrease the sample size used for quality testing.
