WGU C784 Applied Healthcare Statistics Pre-Assessment — 2026/2027 OA Prep 80 Questions • A+ Answers with Rationales
WGU C784 Applied Healthcare Statistics Pre-Assessment
Complete 2026/2027 Question Set with A+ Answers
Western Governors University (WGU) • Objective Assessment (OA) Prep • Competency-Aligned Practice
Directions: This 80-question pre-assessment mirrors the WGU C784 Applied Healthcare Statistics objective assessment blueprint
for the 2026/2027 cycle. Each item has one best answer. Items test descriptive and inferential statistics, levels of measurement,
sampling and study design, probability and distributions, the Central Limit Theorem, confidence intervals, hypothesis testing,
t-tests, ANOVA, chi-square, correlation/regression, and healthcare applications (sensitivity, specificity, PPV/NPV, NNT, relative
risk, odds ratio). Rationales include step-by-step calculations and OA readiness coaching notes highlighting common pitfalls.
Section 1: Introduction to Statistics and Data Types (Descriptive vs. Inferential, Variables, &
Levels of Measurement) — Questions 1–8
Q1: A hospital administrator calculates the average length of stay for all 1,200 patients discharged in the past
month and reports it in a board meeting. This is an example of which type of statistics?
A. Inferential statistics, because the administrator is generalizing to future patients.
B. Descriptive statistics, because the calculation summarizes data from the entire group of interest without
inferring beyond it. [CORRECT]
C. Bayesian statistics, because probabilities are being updated.
D. Predictive statistics, because future discharges are being forecasted.
Correct Answer: B
Rationale: Descriptive statistics organize, summarize, and present data from a group — computing a mean LOS for the 1,200
actual discharges fits perfectly. Inferential statistics would use a sample to estimate or test a claim about a larger population.
Bayesian and predictive statistics are not standard categories at the C784 level. OA readiness: 'summarize the data we already have
= descriptive'; 'use a sample to generalize = inferential.'
Q2: A researcher uses blood pressure measurements from a sample of 200 patients to estimate the average systolic
blood pressure of all adults in a city. This is an example of:
A. Descriptive statistics, because blood pressure is being measured.
B. Inferential statistics, because a sample is being used to draw a conclusion about a larger population.
[CORRECT]
C. Exploratory statistics, because no hypothesis is tested.
D. Categorical statistics, because blood pressure is a category.
Correct Answer: B
Rationale: Inferential statistics use sample data to make generalizations (estimates or tests) about a population. The mean systolic
BP of 200 patients is a sample statistic used to estimate the population parameter for all adults in the city. Descriptive statistics
alone would only summarize the 200 patients. OA readiness: 'sample → population = inferential.'
Q3: Which of the following variables is quantitative and continuous?
A. Blood type (A, B, AB, O).
B. Number of admissions to an ED in a day.
C. Body temperature in degrees Celsius. [CORRECT]
D. Patient satisfaction rating (1–5 Likert scale).
Correct Answer: C
Page 1 — WGU C784 | Western Governors University | Applied Healthcare Statistics
,WGU C784 Applied Healthcare Statistics Pre-Assessment — 2026/2027 OA Prep 80 Questions • A+ Answers with Rationales
Rationale: Body temperature measured on a continuous scale (degrees Celsius) can take any value within a range, including
decimals, making it quantitative and continuous. Blood type is qualitative (nominal). Number of ED admissions is quantitative but
discrete (whole-number counts). A Likert rating is ordinal (qualitative). OA readiness: 'measurable numeric with decimals =
continuous'; 'counted whole numbers = discrete'; 'labels = qualitative.'
Q4: A researcher records each patient's cancer stage as I, II, III, or IV. Which level of measurement does this
represent?
A. Nominal, because stage is a label.
B. Ordinal, because the categories have a meaningful rank order but intervals between stages are not
necessarily equal. [CORRECT]
C. Interval, because the difference between stages is equal.
D. Ratio, because stage IV is twice as severe as stage II.
Correct Answer: B
Rationale: Cancer stages I–IV are ordered categories with a meaningful rank, but the 'distance' between stages is not necessarily
equal and there is no true zero — this is ordinal. Nominal lacks order; interval requires equal intervals with no true zero; ratio
requires equal intervals and a true zero. OA readiness: 'ranked but unequal intervals = ordinal.'
Q5: Temperature in degrees Fahrenheit is an example of which level of measurement?
A. Nominal.
B. Ordinal.
C. Interval, because intervals between degrees are equal but zero is arbitrary (not the absence of heat).
[CORRECT]
D. Ratio, because zero represents the absence of temperature.
Correct Answer: C
Rationale: Fahrenheit (and Celsius) has equal intervals between degrees but an arbitrary zero point (0°F is not 'no heat') — this is
the interval level. Ratio requires a true zero (e.g., Kelvin, weight, height). Nominal and ordinal do not apply. OA readiness: 'equal
intervals + arbitrary zero = interval; equal intervals + true zero = ratio.'
Q6: Which of the following is measured at the ratio level?
A. Patient body temperature in Celsius.
B. Apgar score (0–10).
C. Length of hospital stay in days. [CORRECT]
D. Calendar year of admission (2024, 2025).
Correct Answer: C
Rationale: Length of stay in days is a quantitative measure with equal intervals and a true zero (zero days = no stay) — ratio level.
Temperature in Celsius is interval (arbitrary zero). Apgar score is ordinal. Calendar year is interval (arbitrary zero at year 0). OA
readiness: 'counted or measured with true zero = ratio.'
Q7: A nurse categorizes patients by triage level: 1 = Resuscitation, 2 = Emergent, 3 = Urgent, 4 = Less Urgent, 5 =
Non-Urgent. What level of measurement is this?
A. Nominal, because the categories are named.
B. Ordinal, because the categories have a meaningful, ranked order but the intervals between levels are not
necessarily equal. [CORRECT]
C. Interval, because the levels have equal spacing.
D. Ratio, because higher numbers mean higher acuity.
Correct Answer: B
Page 2 — WGU C784 | Western Governors University | Applied Healthcare Statistics
, WGU C784 Applied Healthcare Statistics Pre-Assessment — 2026/2027 OA Prep 80 Questions • A+ Answers with Rationales
Rationale: Triage levels are ordered categories (1 is more urgent than 2, etc.), but the intervals between levels are not equal (the
clinical difference between 1 and 2 is not the same as between 4 and 5) and there is no true zero — ordinal. OA readiness: triage,
Apgar, Likert, cancer stage, and pain scale are classic ordinal examples.
Q8: Which scenario distinguishes a population parameter from a sample statistic?
A. A parameter is computed from a sample; a statistic is computed from a population.
B. A parameter is a characteristic of an entire population (e.g., the mean BP of all U.S. adults); a statistic is a
characteristic of a sample (e.g., the mean BP of 200 sampled adults). [CORRECT]
C. A parameter is always larger than a statistic.
D. A parameter is qualitative; a statistic is quantitative.
Correct Answer: B
Rationale: By convention, a parameter describes a population (often denoted with Greek letters such as μ, σ, p), and a statistic
describes a sample (denoted with Latin letters such as x̄, s, p̂). Magnitude and qualitative/quantitative nature are not the distinction.
OA readiness: 'population → parameter (Greek); sample → statistic (Latin).'
Section 2: Data Collection, Sampling, and Study Design (Sampling Methods, Bias, &
Experimental Design) — Questions 9–17
Q9: A researcher randomly selects 10 hospitals from a national list, then surveys every nurse employed at those 10
hospitals. This is an example of which sampling method?
A. Simple random sampling.
B. Stratified random sampling.
C. Cluster sampling, because entire groups (clusters) are randomly selected and all members within selected
clusters are surveyed. [CORRECT]
D. Systematic sampling.
Correct Answer: C
Rationale: Cluster sampling randomly selects naturally occurring groups (clusters, e.g., hospitals) and surveys all (or a sample of)
members within selected clusters. Simple random sampling selects individuals directly. Stratified sampling divides the population
into strata and samples from each. Systematic sampling uses a fixed interval. OA readiness: 'whole groups chosen at random =
cluster.'
Q10: A researcher wants to ensure representation from each of five hospital units (ICU, ED, Med-Surg, OB,
Psych). She randomly samples 20 nurses from each unit. This is an example of:
A. Simple random sampling.
B. Stratified random sampling, because the population is divided into subgroups (strata) and random samples
are drawn from each stratum. [CORRECT]
C. Cluster sampling.
D. Convenience sampling.
Correct Answer: B
Rationale: Stratified random sampling divides the population into mutually exclusive strata (here, hospital units) and draws a
random sample from each, ensuring subgroup representation. Cluster samples whole groups; simple random sampling ignores
subgroup structure; convenience is non-random. OA readiness: 'guaranteed subgroup representation = stratified.'
Q11: Every 25th patient admitted to a hospital is selected for a chart review. This is which type of sampling?
A. Simple random sampling.
B. Systematic sampling, because every kth member of the population is selected after a random start.
[CORRECT]
Page 3 — WGU C784 | Western Governors University | Applied Healthcare Statistics
WGU C784 Applied Healthcare Statistics Pre-Assessment
Complete 2026/2027 Question Set with A+ Answers
Western Governors University (WGU) • Objective Assessment (OA) Prep • Competency-Aligned Practice
Directions: This 80-question pre-assessment mirrors the WGU C784 Applied Healthcare Statistics objective assessment blueprint
for the 2026/2027 cycle. Each item has one best answer. Items test descriptive and inferential statistics, levels of measurement,
sampling and study design, probability and distributions, the Central Limit Theorem, confidence intervals, hypothesis testing,
t-tests, ANOVA, chi-square, correlation/regression, and healthcare applications (sensitivity, specificity, PPV/NPV, NNT, relative
risk, odds ratio). Rationales include step-by-step calculations and OA readiness coaching notes highlighting common pitfalls.
Section 1: Introduction to Statistics and Data Types (Descriptive vs. Inferential, Variables, &
Levels of Measurement) — Questions 1–8
Q1: A hospital administrator calculates the average length of stay for all 1,200 patients discharged in the past
month and reports it in a board meeting. This is an example of which type of statistics?
A. Inferential statistics, because the administrator is generalizing to future patients.
B. Descriptive statistics, because the calculation summarizes data from the entire group of interest without
inferring beyond it. [CORRECT]
C. Bayesian statistics, because probabilities are being updated.
D. Predictive statistics, because future discharges are being forecasted.
Correct Answer: B
Rationale: Descriptive statistics organize, summarize, and present data from a group — computing a mean LOS for the 1,200
actual discharges fits perfectly. Inferential statistics would use a sample to estimate or test a claim about a larger population.
Bayesian and predictive statistics are not standard categories at the C784 level. OA readiness: 'summarize the data we already have
= descriptive'; 'use a sample to generalize = inferential.'
Q2: A researcher uses blood pressure measurements from a sample of 200 patients to estimate the average systolic
blood pressure of all adults in a city. This is an example of:
A. Descriptive statistics, because blood pressure is being measured.
B. Inferential statistics, because a sample is being used to draw a conclusion about a larger population.
[CORRECT]
C. Exploratory statistics, because no hypothesis is tested.
D. Categorical statistics, because blood pressure is a category.
Correct Answer: B
Rationale: Inferential statistics use sample data to make generalizations (estimates or tests) about a population. The mean systolic
BP of 200 patients is a sample statistic used to estimate the population parameter for all adults in the city. Descriptive statistics
alone would only summarize the 200 patients. OA readiness: 'sample → population = inferential.'
Q3: Which of the following variables is quantitative and continuous?
A. Blood type (A, B, AB, O).
B. Number of admissions to an ED in a day.
C. Body temperature in degrees Celsius. [CORRECT]
D. Patient satisfaction rating (1–5 Likert scale).
Correct Answer: C
Page 1 — WGU C784 | Western Governors University | Applied Healthcare Statistics
,WGU C784 Applied Healthcare Statistics Pre-Assessment — 2026/2027 OA Prep 80 Questions • A+ Answers with Rationales
Rationale: Body temperature measured on a continuous scale (degrees Celsius) can take any value within a range, including
decimals, making it quantitative and continuous. Blood type is qualitative (nominal). Number of ED admissions is quantitative but
discrete (whole-number counts). A Likert rating is ordinal (qualitative). OA readiness: 'measurable numeric with decimals =
continuous'; 'counted whole numbers = discrete'; 'labels = qualitative.'
Q4: A researcher records each patient's cancer stage as I, II, III, or IV. Which level of measurement does this
represent?
A. Nominal, because stage is a label.
B. Ordinal, because the categories have a meaningful rank order but intervals between stages are not
necessarily equal. [CORRECT]
C. Interval, because the difference between stages is equal.
D. Ratio, because stage IV is twice as severe as stage II.
Correct Answer: B
Rationale: Cancer stages I–IV are ordered categories with a meaningful rank, but the 'distance' between stages is not necessarily
equal and there is no true zero — this is ordinal. Nominal lacks order; interval requires equal intervals with no true zero; ratio
requires equal intervals and a true zero. OA readiness: 'ranked but unequal intervals = ordinal.'
Q5: Temperature in degrees Fahrenheit is an example of which level of measurement?
A. Nominal.
B. Ordinal.
C. Interval, because intervals between degrees are equal but zero is arbitrary (not the absence of heat).
[CORRECT]
D. Ratio, because zero represents the absence of temperature.
Correct Answer: C
Rationale: Fahrenheit (and Celsius) has equal intervals between degrees but an arbitrary zero point (0°F is not 'no heat') — this is
the interval level. Ratio requires a true zero (e.g., Kelvin, weight, height). Nominal and ordinal do not apply. OA readiness: 'equal
intervals + arbitrary zero = interval; equal intervals + true zero = ratio.'
Q6: Which of the following is measured at the ratio level?
A. Patient body temperature in Celsius.
B. Apgar score (0–10).
C. Length of hospital stay in days. [CORRECT]
D. Calendar year of admission (2024, 2025).
Correct Answer: C
Rationale: Length of stay in days is a quantitative measure with equal intervals and a true zero (zero days = no stay) — ratio level.
Temperature in Celsius is interval (arbitrary zero). Apgar score is ordinal. Calendar year is interval (arbitrary zero at year 0). OA
readiness: 'counted or measured with true zero = ratio.'
Q7: A nurse categorizes patients by triage level: 1 = Resuscitation, 2 = Emergent, 3 = Urgent, 4 = Less Urgent, 5 =
Non-Urgent. What level of measurement is this?
A. Nominal, because the categories are named.
B. Ordinal, because the categories have a meaningful, ranked order but the intervals between levels are not
necessarily equal. [CORRECT]
C. Interval, because the levels have equal spacing.
D. Ratio, because higher numbers mean higher acuity.
Correct Answer: B
Page 2 — WGU C784 | Western Governors University | Applied Healthcare Statistics
, WGU C784 Applied Healthcare Statistics Pre-Assessment — 2026/2027 OA Prep 80 Questions • A+ Answers with Rationales
Rationale: Triage levels are ordered categories (1 is more urgent than 2, etc.), but the intervals between levels are not equal (the
clinical difference between 1 and 2 is not the same as between 4 and 5) and there is no true zero — ordinal. OA readiness: triage,
Apgar, Likert, cancer stage, and pain scale are classic ordinal examples.
Q8: Which scenario distinguishes a population parameter from a sample statistic?
A. A parameter is computed from a sample; a statistic is computed from a population.
B. A parameter is a characteristic of an entire population (e.g., the mean BP of all U.S. adults); a statistic is a
characteristic of a sample (e.g., the mean BP of 200 sampled adults). [CORRECT]
C. A parameter is always larger than a statistic.
D. A parameter is qualitative; a statistic is quantitative.
Correct Answer: B
Rationale: By convention, a parameter describes a population (often denoted with Greek letters such as μ, σ, p), and a statistic
describes a sample (denoted with Latin letters such as x̄, s, p̂). Magnitude and qualitative/quantitative nature are not the distinction.
OA readiness: 'population → parameter (Greek); sample → statistic (Latin).'
Section 2: Data Collection, Sampling, and Study Design (Sampling Methods, Bias, &
Experimental Design) — Questions 9–17
Q9: A researcher randomly selects 10 hospitals from a national list, then surveys every nurse employed at those 10
hospitals. This is an example of which sampling method?
A. Simple random sampling.
B. Stratified random sampling.
C. Cluster sampling, because entire groups (clusters) are randomly selected and all members within selected
clusters are surveyed. [CORRECT]
D. Systematic sampling.
Correct Answer: C
Rationale: Cluster sampling randomly selects naturally occurring groups (clusters, e.g., hospitals) and surveys all (or a sample of)
members within selected clusters. Simple random sampling selects individuals directly. Stratified sampling divides the population
into strata and samples from each. Systematic sampling uses a fixed interval. OA readiness: 'whole groups chosen at random =
cluster.'
Q10: A researcher wants to ensure representation from each of five hospital units (ICU, ED, Med-Surg, OB,
Psych). She randomly samples 20 nurses from each unit. This is an example of:
A. Simple random sampling.
B. Stratified random sampling, because the population is divided into subgroups (strata) and random samples
are drawn from each stratum. [CORRECT]
C. Cluster sampling.
D. Convenience sampling.
Correct Answer: B
Rationale: Stratified random sampling divides the population into mutually exclusive strata (here, hospital units) and draws a
random sample from each, ensuring subgroup representation. Cluster samples whole groups; simple random sampling ignores
subgroup structure; convenience is non-random. OA readiness: 'guaranteed subgroup representation = stratified.'
Q11: Every 25th patient admitted to a hospital is selected for a chart review. This is which type of sampling?
A. Simple random sampling.
B. Systematic sampling, because every kth member of the population is selected after a random start.
[CORRECT]
Page 3 — WGU C784 | Western Governors University | Applied Healthcare Statistics
