BUS5112 Quantitative Research Methods Units 5-8 Test Bank —
Statistics, Hypothesis Testing, Regression, and Reporting
Course:
BUS5112 Quantitative Research Methods — University of the People (UoPeople)
Level:
MBA
Year:
2025/2026
Format:
Comprehensive Test Bank — 60 Q&A with Verified Answers
BUS5112 Units 5-8 Test Bank
60 Questions with Verified Correct Answers | 100% Complete Solutions
Question 1 — Unit 5:
A marketing manager at a retail chain is analyzing the daily sales data for a newly launched
product across 50 different store locations. The data shows a mean of 120 units sold and a median
of 85 units. What does this relationship between the mean and median indicate about the
distribution of daily sales?
A) The sales data is perfectly symmetrical across all stores.
B) The sales data is negatively skewed, indicating most stores have very high sales.
C) The sales data is positively skewed, suggesting a few stores have exceptionally high sales.
D) The sales data follows a uniform distribution across all locations.
Answer: C
Explanation:
When the mean is significantly greater than the median, the distribution is positively skewed
(right-skewed). This implies that while the typical store sells around 85 units, a few outlier stores
with extremely high sales are pulling the average up to 120.
Question 2 — Unit 5:
,In a dataset measuring the annual income of employees within a large corporation, the standard
deviation is reported to be very large relative to the mean. What is the most appropriate
interpretation of this statistic for an HR analyst?
A) All employees earn roughly the same salary.
B) There is a high degree of variability or dispersion in employee incomes.
C) The data is tightly clustered around the median income.
D) The company's payroll system has recorded errors in data entry.
Answer: B
Explanation:
Standard deviation measures the amount of variation or dispersion of a set of values. A large
standard deviation relative to the mean indicates that the data points (incomes) are spread out
over a wider range of values, signifying high income inequality or variability within the company.
Question 3 — Unit 5:
A researcher calculating the correlation coefficient between the hours of employee training and
the number of workplace accidents finds an r value of -0.85. How should management interpret
this finding?
A) Training causes a decrease in workplace accidents.
B) There is a strong negative linear relationship, suggesting more training is associated with fewer
accidents.
C) There is a weak negative relationship; training has little association with accident rates.
D) 85% of workplace accidents are caused by a lack of training.
Answer: B
Explanation:
A correlation coefficient (r) of -0.85 indicates a strong negative linear relationship. It means that as
the variable "hours of training" increases, the variable "number of accidents" tends to decrease.
However, it does not inherently prove causation (ruling out A).
Question 4 — Unit 5:
Which descriptive statistic is most robust (least affected) by the presence of extreme outliers in a
financial dataset evaluating startup valuations?
A) The arithmetic mean
B) The variance
C) The interquartile range (IQR)
, D) The range
Answer: C
Explanation:
The interquartile range (IQR) measures the spread of the middle 50% of the data and is resistant
to outliers. The mean, variance, and range are all highly sensitive to extreme values, which can
distort the analysis of startup valuations where a few "unicorns" exist.
Question 5 — Unit 5:
A supply chain analyst finds that the correlation between shipping delays (in days) and customer
satisfaction scores is 0.05. What is the most reasonable business conclusion?
A) There is practically no linear relationship between shipping delays and customer satisfaction.
B) Shipping delays strongly decrease customer satisfaction.
C) Increasing shipping delays slightly improves customer satisfaction.
D) The calculation must be incorrect as delays always impact satisfaction.
Answer: A
Explanation:
A correlation coefficient near 0 (like 0.05) indicates the absence of a linear relationship between
the two variables. In this specific dataset, changes in shipping delays do not linearly correlate with
changes in customer satisfaction scores.
Question 6 — Unit 5:
When constructing a frequency distribution for continuous data, such as the exact weight of
manufactured components, what is a critical step to ensure meaningful interpretation?
A) Listing every single observed exact weight.
B) Grouping the data into mutually exclusive and exhaustive classes or bins.
C) Only recording the highest and lowest values.
D) Converting all weights to nominal categorical variables.
Answer: B
Explanation:
For continuous data, creating a frequency distribution requires grouping the infinite possible
values into distinct classes or bins. This condenses the data into a readable format, allowing
analysts to see patterns, central tendencies, and the shape of the distribution.
Statistics, Hypothesis Testing, Regression, and Reporting
Course:
BUS5112 Quantitative Research Methods — University of the People (UoPeople)
Level:
MBA
Year:
2025/2026
Format:
Comprehensive Test Bank — 60 Q&A with Verified Answers
BUS5112 Units 5-8 Test Bank
60 Questions with Verified Correct Answers | 100% Complete Solutions
Question 1 — Unit 5:
A marketing manager at a retail chain is analyzing the daily sales data for a newly launched
product across 50 different store locations. The data shows a mean of 120 units sold and a median
of 85 units. What does this relationship between the mean and median indicate about the
distribution of daily sales?
A) The sales data is perfectly symmetrical across all stores.
B) The sales data is negatively skewed, indicating most stores have very high sales.
C) The sales data is positively skewed, suggesting a few stores have exceptionally high sales.
D) The sales data follows a uniform distribution across all locations.
Answer: C
Explanation:
When the mean is significantly greater than the median, the distribution is positively skewed
(right-skewed). This implies that while the typical store sells around 85 units, a few outlier stores
with extremely high sales are pulling the average up to 120.
Question 2 — Unit 5:
,In a dataset measuring the annual income of employees within a large corporation, the standard
deviation is reported to be very large relative to the mean. What is the most appropriate
interpretation of this statistic for an HR analyst?
A) All employees earn roughly the same salary.
B) There is a high degree of variability or dispersion in employee incomes.
C) The data is tightly clustered around the median income.
D) The company's payroll system has recorded errors in data entry.
Answer: B
Explanation:
Standard deviation measures the amount of variation or dispersion of a set of values. A large
standard deviation relative to the mean indicates that the data points (incomes) are spread out
over a wider range of values, signifying high income inequality or variability within the company.
Question 3 — Unit 5:
A researcher calculating the correlation coefficient between the hours of employee training and
the number of workplace accidents finds an r value of -0.85. How should management interpret
this finding?
A) Training causes a decrease in workplace accidents.
B) There is a strong negative linear relationship, suggesting more training is associated with fewer
accidents.
C) There is a weak negative relationship; training has little association with accident rates.
D) 85% of workplace accidents are caused by a lack of training.
Answer: B
Explanation:
A correlation coefficient (r) of -0.85 indicates a strong negative linear relationship. It means that as
the variable "hours of training" increases, the variable "number of accidents" tends to decrease.
However, it does not inherently prove causation (ruling out A).
Question 4 — Unit 5:
Which descriptive statistic is most robust (least affected) by the presence of extreme outliers in a
financial dataset evaluating startup valuations?
A) The arithmetic mean
B) The variance
C) The interquartile range (IQR)
, D) The range
Answer: C
Explanation:
The interquartile range (IQR) measures the spread of the middle 50% of the data and is resistant
to outliers. The mean, variance, and range are all highly sensitive to extreme values, which can
distort the analysis of startup valuations where a few "unicorns" exist.
Question 5 — Unit 5:
A supply chain analyst finds that the correlation between shipping delays (in days) and customer
satisfaction scores is 0.05. What is the most reasonable business conclusion?
A) There is practically no linear relationship between shipping delays and customer satisfaction.
B) Shipping delays strongly decrease customer satisfaction.
C) Increasing shipping delays slightly improves customer satisfaction.
D) The calculation must be incorrect as delays always impact satisfaction.
Answer: A
Explanation:
A correlation coefficient near 0 (like 0.05) indicates the absence of a linear relationship between
the two variables. In this specific dataset, changes in shipping delays do not linearly correlate with
changes in customer satisfaction scores.
Question 6 — Unit 5:
When constructing a frequency distribution for continuous data, such as the exact weight of
manufactured components, what is a critical step to ensure meaningful interpretation?
A) Listing every single observed exact weight.
B) Grouping the data into mutually exclusive and exhaustive classes or bins.
C) Only recording the highest and lowest values.
D) Converting all weights to nominal categorical variables.
Answer: B
Explanation:
For continuous data, creating a frequency distribution requires grouping the infinite possible
values into distinct classes or bins. This condenses the data into a readable format, allowing
analysts to see patterns, central tendencies, and the shape of the distribution.
