D315 ITEC 2112 Network & Security -
Foundations
Final Assessment Review
(Questions & Solutions)
2025
©2025
, Multiple Choice Questions (Questions 1–10)
1. Case Study – Sampling Distribution in Market Research
A market research firm samples customer satisfaction scores for a new
product. They repeatedly take samples of size 50 from the customer
pool. The firm notices that the distribution of the sample means is
approximately normal, regardless of the original population distribution.
Question: This finding is best explained by:
A. The Law of Large Numbers
B. The Central Limit Theorem
C. Sampling bias
D. Random error reduction
ANS: B. The Central Limit Theorem
Rationale: The Central Limit Theorem states that the distribution of
sample means will tend toward a normal distribution as the sample size
increases, regardless of the population’s distribution. This underpins
many inferential methods in business statistics.
---
2. Case Study – Confidence Interval Interpretation for Sales Forecasts
A business analyst calculates a 95% confidence interval for the mean
weekly sales of a product as \$32,000 to \$38,000.
Question: Which of the following interpretations is correct?
A. There is a 95% probability that the true mean falls between \$32,000
and \$38,000.
B. 95% of the weekly sales figures fall between \$32,000 and \$38,000.
C. If the study were repeated, 95% of the confidence intervals would
contain the true mean.
D. There is a 5% chance that the mean weekly sales fall outside this
range.
ANS: C. If the study were repeated, 95% of the confidence intervals
would contain the true mean.
©2025
, Rationale: Confidence intervals reflect the long-run performance of the
estimation process—they do not assign a probability to the parameter
itself.
---
3. Case Study – Hypothesis Testing in Product Quality
A company claims that its newly produced smartphone has an average
battery life of at least 12 hours. A quality control analyst tests a sample of
40 smartphones and obtains a sample mean of 11.5 hours with a small
standard error.
Question: If the null hypothesis states that the mean battery life is 12
hours, which error might occur if the analyst concludes that the
smartphones do not meet the claim when they actually do?
A. Type I error
B. Type II error
C. Sampling error
D. Nonsampling error
ANS: A. Type I error
Rationale: A Type I error occurs when the null hypothesis is rejected
when it is actually true—in this case, concluding that battery life is less
than 12 hours when it is not.
---
4. Case Study – p-Values in Business Analytics
During a study comparing two marketing strategies, an analyst obtains a
p-value of 0.03 when testing for differences in average sales.
Question: What does a p-value of 0.03 most directly indicate?
A. There is a 3% chance that the null hypothesis is true.
B. There is a 97% probability that the alternative hypothesis is true.
C. The observed data would occur 3% of the time if the null hypothesis
were true.
D. The difference in sales is practically significant.
ANS: C. The observed data would occur 3% of the time if the null
©2025
Foundations
Final Assessment Review
(Questions & Solutions)
2025
©2025
, Multiple Choice Questions (Questions 1–10)
1. Case Study – Sampling Distribution in Market Research
A market research firm samples customer satisfaction scores for a new
product. They repeatedly take samples of size 50 from the customer
pool. The firm notices that the distribution of the sample means is
approximately normal, regardless of the original population distribution.
Question: This finding is best explained by:
A. The Law of Large Numbers
B. The Central Limit Theorem
C. Sampling bias
D. Random error reduction
ANS: B. The Central Limit Theorem
Rationale: The Central Limit Theorem states that the distribution of
sample means will tend toward a normal distribution as the sample size
increases, regardless of the population’s distribution. This underpins
many inferential methods in business statistics.
---
2. Case Study – Confidence Interval Interpretation for Sales Forecasts
A business analyst calculates a 95% confidence interval for the mean
weekly sales of a product as \$32,000 to \$38,000.
Question: Which of the following interpretations is correct?
A. There is a 95% probability that the true mean falls between \$32,000
and \$38,000.
B. 95% of the weekly sales figures fall between \$32,000 and \$38,000.
C. If the study were repeated, 95% of the confidence intervals would
contain the true mean.
D. There is a 5% chance that the mean weekly sales fall outside this
range.
ANS: C. If the study were repeated, 95% of the confidence intervals
would contain the true mean.
©2025
, Rationale: Confidence intervals reflect the long-run performance of the
estimation process—they do not assign a probability to the parameter
itself.
---
3. Case Study – Hypothesis Testing in Product Quality
A company claims that its newly produced smartphone has an average
battery life of at least 12 hours. A quality control analyst tests a sample of
40 smartphones and obtains a sample mean of 11.5 hours with a small
standard error.
Question: If the null hypothesis states that the mean battery life is 12
hours, which error might occur if the analyst concludes that the
smartphones do not meet the claim when they actually do?
A. Type I error
B. Type II error
C. Sampling error
D. Nonsampling error
ANS: A. Type I error
Rationale: A Type I error occurs when the null hypothesis is rejected
when it is actually true—in this case, concluding that battery life is less
than 12 hours when it is not.
---
4. Case Study – p-Values in Business Analytics
During a study comparing two marketing strategies, an analyst obtains a
p-value of 0.03 when testing for differences in average sales.
Question: What does a p-value of 0.03 most directly indicate?
A. There is a 3% chance that the null hypothesis is true.
B. There is a 97% probability that the alternative hypothesis is true.
C. The observed data would occur 3% of the time if the null hypothesis
were true.
D. The difference in sales is practically significant.
ANS: C. The observed data would occur 3% of the time if the null
©2025
