Business Analytics MBA 2025 — 55 Q&A Complete Study Guide
UoPeople BUS5111
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
UoPeople MBA
Year:
2025/2026
Format:
55 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
Question 1
A global health logistics manager needs to assess inventory shrink rates across international
supply hubs. To guarantee proportional geographic representation, she categorizes all distribution
centres by their respective continents and subsequently draws a randomized subset from within
every continental category. Which sampling strategy is being applied?
A) Basic randomized selection
B) Cluster-based sampling
C) Stratified selection technique
D) Convenience-based polling
,Answer: C
Rationale:
Lead: Stratified sampling is executed by dividing a heterogeneous population into distinct, non-
overlapping homogeneous subgroups (strata) and then drawing a random sample from within
every single subgroup.
Discriminator: The explicit categorisation into continents (the strata) followed by sampling within*
every continent ensures proportional representation, which is the defining hallmark of this
technique.
Distractor: Cluster-based sampling (Option B) is highly tempting but incorrect; it would involve
randomly selecting a few entire continents and ignoring the rest completely, rather than polling
a subset from all of them.
Examiner Insight: Stratification is mathematically superior to basic randomization when intra-
group variation is minimal but inter-group variation is substantial. [INFORMS Data Standards
2025]
Question 2
A private digital health startup is evaluating the age demographic of its premium longevity app
subscribers. The dataset is heavily right-skewed, skewed by a small cohort of affluent users over
the age of 85. Which statistical measure of central tendency provides the most accurate reflection
of the "typical" subscriber's age?
A) Arithmetic mean
B) Median value
C) Most frequent mode
D) Standard deviation
Answer: B
Rationale:
Lead: The median isolates the exact midpoint of an ordered dataset, rendering it highly
resistant to the mathematical distortion caused by extreme outliers.
Discriminator: The explicit mention of a "heavily right-skewed" distribution directly mandates
the use of the median to represent central tendency accurately.
Distractor: The arithmetic mean (Option A) is incorrect because it is artificially dragged upward
by the right-sided outliers (the 85+ cohort), falsely elevating the perceived average age.
High-Yield Point: Whenever clinical or financial datasets present significant skewness (e.g.,
length of stay, income, age), the median is the mandatory standard for reporting. [NICE
, Evidence Standards 2025]
Question 3
A hospital operations director notes that daily emergency admissions follow a normal distribution,
with a mean of 5,000 patients across the trust and a standard deviation of 500. Approximately
what percentage of days will record between 4,500 and 5,500 admissions?
A) 50%
B) 68%
C) 95%
D) 99.7%
Answer: B
Rationale:
Lead: According to the empirical rule (the 68-95-99.7 rule) for normally distributed data,
approximately 68% of all values fall within exactly one standard deviation above and below the
mean.
Discriminator: The target range of 4,500 to 5,500 is calculated by taking the mean (5,000) and
adding/subtracting one standard deviation (500), pointing definitively to 68%.
Distractor: Option C (95%) is incorrect as it represents two standard deviations from the mean
(which would span from 4,000 to 6,000 admissions).
Clinical Pearl: The empirical rule is a rapid triage tool for identifying operational anomalies;
days falling outside two standard deviations trigger immediate resource escalation. [NHS
Operational Guidelines 2024]
Question 4
A financial institution deploys a machine learning model to automate credit approvals. A
subsequent compliance audit reveals that the algorithm systematically denies loans to applicants
residing in specific urban postal codes, despite identical income brackets. Which ethical data
vulnerability does this highlight?
A) Unauthorised data breach
B) Algorithmic bias
C) Corporate espionage
D) Cryptographic failure
Answer: B
, Rationale:
Lead: Algorithmic bias manifests when an artificial intelligence system generates systematically
prejudiced outputs driven by flawed assumptions or unrepresentative training data.
Discriminator: The model is using postal codes as an implicit proxy variable for socioeconomic
or racial demographics, resulting in discriminatory lending practices.
Distractor: Unauthorised data breach (Option A) is incorrect because the scenario describes
the model misapplying legally acquired data, not the theft or exposure of that data.
Key Principle: Modern regulatory frameworks rigorously penalize the use of proxy variables
that lead to unintended demographic discrimination in AI models. [NIST AI RMF 2024]
Question 5
An outpatient clinic manager wants to visualize the frequency distribution of continuous patient
wait times (measured in minutes) over the last fiscal year. The goal is to highlight the most
common time intervals before a patient sees a doctor. Which graphical tool is optimal?
A) Scatter matrix
B) Categorical pie chart
C) Histogram
D) Trendline graph
Answer: C
Rationale:
Lead: A histogram aggregates continuous numerical data into sequential intervals (bins) and
uses vertical bars to display the frequency distribution of data falling into each bin.
Discriminator: The specific requirement to group "continuous" data (wait times) into "intervals"
to show frequency perfectly aligns with the function of a histogram.
Distractor: A scatter matrix (Option A) fails here; it is utilized to visualize the correlation
between two distinct numerical variables, not the frequency distribution of a single variable.
Examiner Insight: While bar charts display categorical data with spaces between bars,
histograms display continuous data with contiguous bars to represent an unbroken number line.
[Tableau Visual Analytics 2025]
Question 6
A regional health authority measures ambulance response times. The performance dashboard
indicates that the 95th percentile for critical call responses is 60 minutes. How should this metric
be interpreted by the clinical board?
UoPeople BUS5111
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
UoPeople MBA
Year:
2025/2026
Format:
55 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
Question 1
A global health logistics manager needs to assess inventory shrink rates across international
supply hubs. To guarantee proportional geographic representation, she categorizes all distribution
centres by their respective continents and subsequently draws a randomized subset from within
every continental category. Which sampling strategy is being applied?
A) Basic randomized selection
B) Cluster-based sampling
C) Stratified selection technique
D) Convenience-based polling
,Answer: C
Rationale:
Lead: Stratified sampling is executed by dividing a heterogeneous population into distinct, non-
overlapping homogeneous subgroups (strata) and then drawing a random sample from within
every single subgroup.
Discriminator: The explicit categorisation into continents (the strata) followed by sampling within*
every continent ensures proportional representation, which is the defining hallmark of this
technique.
Distractor: Cluster-based sampling (Option B) is highly tempting but incorrect; it would involve
randomly selecting a few entire continents and ignoring the rest completely, rather than polling
a subset from all of them.
Examiner Insight: Stratification is mathematically superior to basic randomization when intra-
group variation is minimal but inter-group variation is substantial. [INFORMS Data Standards
2025]
Question 2
A private digital health startup is evaluating the age demographic of its premium longevity app
subscribers. The dataset is heavily right-skewed, skewed by a small cohort of affluent users over
the age of 85. Which statistical measure of central tendency provides the most accurate reflection
of the "typical" subscriber's age?
A) Arithmetic mean
B) Median value
C) Most frequent mode
D) Standard deviation
Answer: B
Rationale:
Lead: The median isolates the exact midpoint of an ordered dataset, rendering it highly
resistant to the mathematical distortion caused by extreme outliers.
Discriminator: The explicit mention of a "heavily right-skewed" distribution directly mandates
the use of the median to represent central tendency accurately.
Distractor: The arithmetic mean (Option A) is incorrect because it is artificially dragged upward
by the right-sided outliers (the 85+ cohort), falsely elevating the perceived average age.
High-Yield Point: Whenever clinical or financial datasets present significant skewness (e.g.,
length of stay, income, age), the median is the mandatory standard for reporting. [NICE
, Evidence Standards 2025]
Question 3
A hospital operations director notes that daily emergency admissions follow a normal distribution,
with a mean of 5,000 patients across the trust and a standard deviation of 500. Approximately
what percentage of days will record between 4,500 and 5,500 admissions?
A) 50%
B) 68%
C) 95%
D) 99.7%
Answer: B
Rationale:
Lead: According to the empirical rule (the 68-95-99.7 rule) for normally distributed data,
approximately 68% of all values fall within exactly one standard deviation above and below the
mean.
Discriminator: The target range of 4,500 to 5,500 is calculated by taking the mean (5,000) and
adding/subtracting one standard deviation (500), pointing definitively to 68%.
Distractor: Option C (95%) is incorrect as it represents two standard deviations from the mean
(which would span from 4,000 to 6,000 admissions).
Clinical Pearl: The empirical rule is a rapid triage tool for identifying operational anomalies;
days falling outside two standard deviations trigger immediate resource escalation. [NHS
Operational Guidelines 2024]
Question 4
A financial institution deploys a machine learning model to automate credit approvals. A
subsequent compliance audit reveals that the algorithm systematically denies loans to applicants
residing in specific urban postal codes, despite identical income brackets. Which ethical data
vulnerability does this highlight?
A) Unauthorised data breach
B) Algorithmic bias
C) Corporate espionage
D) Cryptographic failure
Answer: B
, Rationale:
Lead: Algorithmic bias manifests when an artificial intelligence system generates systematically
prejudiced outputs driven by flawed assumptions or unrepresentative training data.
Discriminator: The model is using postal codes as an implicit proxy variable for socioeconomic
or racial demographics, resulting in discriminatory lending practices.
Distractor: Unauthorised data breach (Option A) is incorrect because the scenario describes
the model misapplying legally acquired data, not the theft or exposure of that data.
Key Principle: Modern regulatory frameworks rigorously penalize the use of proxy variables
that lead to unintended demographic discrimination in AI models. [NIST AI RMF 2024]
Question 5
An outpatient clinic manager wants to visualize the frequency distribution of continuous patient
wait times (measured in minutes) over the last fiscal year. The goal is to highlight the most
common time intervals before a patient sees a doctor. Which graphical tool is optimal?
A) Scatter matrix
B) Categorical pie chart
C) Histogram
D) Trendline graph
Answer: C
Rationale:
Lead: A histogram aggregates continuous numerical data into sequential intervals (bins) and
uses vertical bars to display the frequency distribution of data falling into each bin.
Discriminator: The specific requirement to group "continuous" data (wait times) into "intervals"
to show frequency perfectly aligns with the function of a histogram.
Distractor: A scatter matrix (Option A) fails here; it is utilized to visualize the correlation
between two distinct numerical variables, not the frequency distribution of a single variable.
Examiner Insight: While bar charts display categorical data with spaces between bars,
histograms display continuous data with contiguous bars to represent an unbroken number line.
[Tableau Visual Analytics 2025]
Question 6
A regional health authority measures ambulance response times. The performance dashboard
indicates that the 95th percentile for critical call responses is 60 minutes. How should this metric
be interpreted by the clinical board?
