WGU C784 APPLIED HEALTHCARE
STATISTICS FINAL EXAM
PREPARATION
1. A researcher measures the body temperature of 50 patients in a clinical trial. Which level
of measurement does this data represent?
A. Nominal
B. Ordinal
C. Interval
D. Ratio
Answer: C
Conceptual Explanation: Temperature in Celsius or Fahrenheit is interval data because
the difference between values is meaningful, but there is no true zero point (0 degrees does
not mean ‘no temperature’).
2. In a study of hospital readmission rates, a researcher selects every 10th patient from a
chronological list. What sampling method is being used?
A. Simple Random Sampling
B. Stratified Sampling
,C. Systematic Sampling
D. Cluster Sampling
Answer: C
Conceptual Explanation: Systematic sampling involves selecting elements from an
ordered population using a fixed periodic interval (the ‘kth’ element).
3. A dataset of patient recovery times (in days) is highly positively skewed. Which measure of
central tendency is most appropriate to describe the ‘typical’ recovery time?
A. Median
B. Mean
C. Mode
D. Standard Deviation
Answer: A
Conceptual Explanation: The median is more robust to outliers and skewness than the
mean, making it the preferred measure for skewed distributions.
4. If the p-value of a clinical trial’s result is 0.03 and the alpha level is set at 0.05, what is the
correct statistical conclusion?
A. Fail to reject the null hypothesis
B. Reject the null hypothesis
C. The result is not statistically significant
, D. Accept the null hypothesis as true
Answer: B
Conceptual Explanation: When the p-value is less than the alpha level (p < 0.05), the
results are statistically significant, and the null hypothesis is rejected.
5. A diagnostic test has high sensitivity. This means the test is particularly good at:
A. Identifying true negatives
B. Avoiding false positives
C. Identifying true positives
D. Predicting the severity of the disease
Answer: C
Conceptual Explanation: Sensitivity (True Positive Rate) measures the proportion of
actual positives that are correctly identified as such by the test.
6. What is the probability of a patient having a specific condition if the incidence rate is 5%
and the diagnostic test has a 10% false positive rate? Assume the patient tests positive.
(Bayes’ Theorem Application)
A. 0.34
B. 0.05
C. 0.50
D. 0.90
STATISTICS FINAL EXAM
PREPARATION
1. A researcher measures the body temperature of 50 patients in a clinical trial. Which level
of measurement does this data represent?
A. Nominal
B. Ordinal
C. Interval
D. Ratio
Answer: C
Conceptual Explanation: Temperature in Celsius or Fahrenheit is interval data because
the difference between values is meaningful, but there is no true zero point (0 degrees does
not mean ‘no temperature’).
2. In a study of hospital readmission rates, a researcher selects every 10th patient from a
chronological list. What sampling method is being used?
A. Simple Random Sampling
B. Stratified Sampling
,C. Systematic Sampling
D. Cluster Sampling
Answer: C
Conceptual Explanation: Systematic sampling involves selecting elements from an
ordered population using a fixed periodic interval (the ‘kth’ element).
3. A dataset of patient recovery times (in days) is highly positively skewed. Which measure of
central tendency is most appropriate to describe the ‘typical’ recovery time?
A. Median
B. Mean
C. Mode
D. Standard Deviation
Answer: A
Conceptual Explanation: The median is more robust to outliers and skewness than the
mean, making it the preferred measure for skewed distributions.
4. If the p-value of a clinical trial’s result is 0.03 and the alpha level is set at 0.05, what is the
correct statistical conclusion?
A. Fail to reject the null hypothesis
B. Reject the null hypothesis
C. The result is not statistically significant
, D. Accept the null hypothesis as true
Answer: B
Conceptual Explanation: When the p-value is less than the alpha level (p < 0.05), the
results are statistically significant, and the null hypothesis is rejected.
5. A diagnostic test has high sensitivity. This means the test is particularly good at:
A. Identifying true negatives
B. Avoiding false positives
C. Identifying true positives
D. Predicting the severity of the disease
Answer: C
Conceptual Explanation: Sensitivity (True Positive Rate) measures the proportion of
actual positives that are correctly identified as such by the test.
6. What is the probability of a patient having a specific condition if the incidence rate is 5%
and the diagnostic test has a 10% false positive rate? Assume the patient tests positive.
(Bayes’ Theorem Application)
A. 0.34
B. 0.05
C. 0.50
D. 0.90
