WGU C784 Applied Healthcare Statistics
Objective Assessment – WGU C784 Study
Guide, Original Practice Questions & Answers,
Objective Assessment Preparation,
Comprehensive Applied Healthcare Statistics
Review, Probability, Descriptive Statistics,
Regression, Correlation, Data Interpretation,
Algebra & Healthcare Statistics
Question 1: A researcher is studying the average systolic blood pressure of
patients in a cardiac unit. The sample mean is 132 mmHg, and the 95%
confidence interval for the population mean is [128, 136]. Which of the
following is the most accurate interpretation of this confidence interval?
A. 95% of all patients in the cardiac unit have a systolic blood pressure between 128 and
136 mmHg.
B. The probability that the true population mean is exactly 132 mmHg is 95%.
C. There is a 95% probability that a randomly selected patient will have a blood pressure
between 128 and 136 mmHg.
D. The researcher is 95% confident that the interval [128, 136] contains the true
population mean systolic blood pressure.
CORRECT ANSWER: D. The researcher is 95% confident that the interval [128,
136] contains the true population mean systolic blood pressure.
Rationale: A confidence interval provides a range of plausible values for a population
parameter. The correct interpretation is that if the sampling process were repeated
many times, approximately 95% of the constructed intervals would capture the true
population mean. The interval does not describe the distribution of individual patient
values.
Question 2: A histogram of patient wait times in an emergency department is
skewed to the right. Which measure of central tendency is most appropriate to
report for this data?
A. Mean
B. Median
C. Mode
D. Range
CORRECT ANSWER: B. Median
Rationale: In a right-skewed distribution, the mean is pulled toward the long tail by
extreme high values, making it less representative of the central location. The median,
,being the 50th percentile, is resistant to skew and outliers, thus providing a more
accurate measure of central tendency for non-normal data.
Question 3: In a clinical trial, a p-value of 0.04 is reported for a two-tailed test
comparing a new drug to a placebo. Using a significance level of α = 0.05, what
is the appropriate conclusion?
A. Fail to reject the null hypothesis; there is no evidence of an effect.
B. Reject the null hypothesis; the result is statistically significant.
C. Accept the null hypothesis; the drug is ineffective.
D. Reject the alternative hypothesis; the effect is clinically negligible.
CORRECT ANSWER: B. Reject the null hypothesis; the result is statistically
significant.
Rationale: The p-value (0.04) is less than the pre-specified significance level (0.05).
Therefore, we reject the null hypothesis. This indicates that the observed difference is
statistically significant, meaning it is unlikely to have occurred by chance alone,
assuming the null hypothesis is true.
Question 4: A study measures the body mass index (BMI) of 50 patients. The
variance of the BMI values is 25 (kg/m²)². What is the standard deviation of
the BMI values?
A. 2 kg/m²
B. 5 kg/m²
C. 25 kg/m²
D. 50 kg/m²
CORRECT ANSWER: B. 5 kg/m²
Rationale: The standard deviation is the square root of the variance. The square root of
25 is 5. Thus, the standard deviation is 5 kg/m². The standard deviation is a measure of
the typical deviation of individual data points from the mean.
Question 5: A nurse records the number of falls that occur per day in a
geriatric ward over a 30-day period. What type of variable is "number of falls
per day"?
A. Categorical nominal
B. Categorical ordinal
C. Continuous quantitative
D. Discrete quantitative
CORRECT ANSWER: D. Discrete quantitative
,Rationale: The number of falls is a quantitative variable because it represents a count. It
is discrete because it can only take on whole, countable values (0, 1, 2, etc.). It cannot be
a fraction. Continuous data can take on any value within a range, such as weight or
temperature.
Question 6: A researcher wants to determine if there is an association between
smoking status (smoker/non-smoker) and the presence of lung disease
(yes/no). Which statistical test is most appropriate for analyzing this data?
A. One-sample t-test
B. Paired t-test
C. Chi-square test of independence
D. Pearson correlation coefficient
CORRECT ANSWER: C. Chi-square test of independence
Rationale: The chi-square test of independence is used to determine if there is a
significant association between two categorical variables. In this case, both variables
(smoking status and lung disease) are dichotomous categorical variables. The test
compares the observed frequencies in each category to the frequencies expected under
independence.
Question 7: A healthcare dataset contains outliers. Which of the following
measures of variability is most robust and unaffected by these extreme values?
A. Range
B. Variance
C. Standard deviation
D. Interquartile range (IQR)
CORRECT ANSWER: D. Interquartile range (IQR)
Rationale: The IQR is a measure of variability based on the range of the middle 50% of
the data. It is calculated as Q3 - Q1. Because it focuses on the central portion of the
dataset, the IQR is largely unaffected by outliers, unlike the range, variance, and
standard deviation, which are all sensitive to extreme values.
Question 8: In a normal distribution, what proportion of data falls within two
standard deviations (z-scores) of the mean?
A. Approximately 68%
B. Approximately 95%
C. Approximately 99.7%
D. Approximately 100%
, CORRECT ANSWER: B. Approximately 95%
Rationale: The empirical rule (68-95-99.7 rule) states that for a normal distribution,
approximately 68% of the data falls within 1 standard deviation of the mean, about 95%
falls within 2 standard deviations, and about 99.7% falls within 3 standard deviations.
Question 9: A study has a sample size of 15. The researcher is testing the
hypothesis that the sample mean is different from a known population mean.
Which test should be used, assuming the population standard deviation is
unknown?
A. z-test
B. Paired t-test
C. One-sample t-test
D. Chi-square test
CORRECT ANSWER: C. One-sample t-test
Rationale: A one-sample t-test is used to compare the mean of a single sample to a
known population mean when the population standard deviation is unknown. It is
appropriate for smaller sample sizes (n < 30), as the t-distribution is used to account for
the extra uncertainty in estimating the standard deviation from the sample.
Question 10: A researcher is studying the correlation between hours of
exercise per week and resting heart rate. The calculated Pearson correlation
coefficient (r) is -0.85. What does this indicate?
A. A weak, positive linear relationship.
B. A strong, positive linear relationship.
C. A weak, negative linear relationship.
D. A strong, negative linear relationship.
CORRECT ANSWER: D. A strong, negative linear relationship.
Rationale: The Pearson correlation coefficient (r) ranges from -1 to +1. A value of -0.85
indicates a strong linear relationship because the absolute value is close to 1. The
negative sign indicates an inverse relationship: as hours of exercise increase, resting
heart rate tends to decrease.
Question 11: A hospital calculates the sensitivity of a new diagnostic test for a
disease. Sensitivity is defined as the probability of:
A. A negative test result given the patient does not have the disease.
B. A positive test result given the patient does not have the disease.
Objective Assessment – WGU C784 Study
Guide, Original Practice Questions & Answers,
Objective Assessment Preparation,
Comprehensive Applied Healthcare Statistics
Review, Probability, Descriptive Statistics,
Regression, Correlation, Data Interpretation,
Algebra & Healthcare Statistics
Question 1: A researcher is studying the average systolic blood pressure of
patients in a cardiac unit. The sample mean is 132 mmHg, and the 95%
confidence interval for the population mean is [128, 136]. Which of the
following is the most accurate interpretation of this confidence interval?
A. 95% of all patients in the cardiac unit have a systolic blood pressure between 128 and
136 mmHg.
B. The probability that the true population mean is exactly 132 mmHg is 95%.
C. There is a 95% probability that a randomly selected patient will have a blood pressure
between 128 and 136 mmHg.
D. The researcher is 95% confident that the interval [128, 136] contains the true
population mean systolic blood pressure.
CORRECT ANSWER: D. The researcher is 95% confident that the interval [128,
136] contains the true population mean systolic blood pressure.
Rationale: A confidence interval provides a range of plausible values for a population
parameter. The correct interpretation is that if the sampling process were repeated
many times, approximately 95% of the constructed intervals would capture the true
population mean. The interval does not describe the distribution of individual patient
values.
Question 2: A histogram of patient wait times in an emergency department is
skewed to the right. Which measure of central tendency is most appropriate to
report for this data?
A. Mean
B. Median
C. Mode
D. Range
CORRECT ANSWER: B. Median
Rationale: In a right-skewed distribution, the mean is pulled toward the long tail by
extreme high values, making it less representative of the central location. The median,
,being the 50th percentile, is resistant to skew and outliers, thus providing a more
accurate measure of central tendency for non-normal data.
Question 3: In a clinical trial, a p-value of 0.04 is reported for a two-tailed test
comparing a new drug to a placebo. Using a significance level of α = 0.05, what
is the appropriate conclusion?
A. Fail to reject the null hypothesis; there is no evidence of an effect.
B. Reject the null hypothesis; the result is statistically significant.
C. Accept the null hypothesis; the drug is ineffective.
D. Reject the alternative hypothesis; the effect is clinically negligible.
CORRECT ANSWER: B. Reject the null hypothesis; the result is statistically
significant.
Rationale: The p-value (0.04) is less than the pre-specified significance level (0.05).
Therefore, we reject the null hypothesis. This indicates that the observed difference is
statistically significant, meaning it is unlikely to have occurred by chance alone,
assuming the null hypothesis is true.
Question 4: A study measures the body mass index (BMI) of 50 patients. The
variance of the BMI values is 25 (kg/m²)². What is the standard deviation of
the BMI values?
A. 2 kg/m²
B. 5 kg/m²
C. 25 kg/m²
D. 50 kg/m²
CORRECT ANSWER: B. 5 kg/m²
Rationale: The standard deviation is the square root of the variance. The square root of
25 is 5. Thus, the standard deviation is 5 kg/m². The standard deviation is a measure of
the typical deviation of individual data points from the mean.
Question 5: A nurse records the number of falls that occur per day in a
geriatric ward over a 30-day period. What type of variable is "number of falls
per day"?
A. Categorical nominal
B. Categorical ordinal
C. Continuous quantitative
D. Discrete quantitative
CORRECT ANSWER: D. Discrete quantitative
,Rationale: The number of falls is a quantitative variable because it represents a count. It
is discrete because it can only take on whole, countable values (0, 1, 2, etc.). It cannot be
a fraction. Continuous data can take on any value within a range, such as weight or
temperature.
Question 6: A researcher wants to determine if there is an association between
smoking status (smoker/non-smoker) and the presence of lung disease
(yes/no). Which statistical test is most appropriate for analyzing this data?
A. One-sample t-test
B. Paired t-test
C. Chi-square test of independence
D. Pearson correlation coefficient
CORRECT ANSWER: C. Chi-square test of independence
Rationale: The chi-square test of independence is used to determine if there is a
significant association between two categorical variables. In this case, both variables
(smoking status and lung disease) are dichotomous categorical variables. The test
compares the observed frequencies in each category to the frequencies expected under
independence.
Question 7: A healthcare dataset contains outliers. Which of the following
measures of variability is most robust and unaffected by these extreme values?
A. Range
B. Variance
C. Standard deviation
D. Interquartile range (IQR)
CORRECT ANSWER: D. Interquartile range (IQR)
Rationale: The IQR is a measure of variability based on the range of the middle 50% of
the data. It is calculated as Q3 - Q1. Because it focuses on the central portion of the
dataset, the IQR is largely unaffected by outliers, unlike the range, variance, and
standard deviation, which are all sensitive to extreme values.
Question 8: In a normal distribution, what proportion of data falls within two
standard deviations (z-scores) of the mean?
A. Approximately 68%
B. Approximately 95%
C. Approximately 99.7%
D. Approximately 100%
, CORRECT ANSWER: B. Approximately 95%
Rationale: The empirical rule (68-95-99.7 rule) states that for a normal distribution,
approximately 68% of the data falls within 1 standard deviation of the mean, about 95%
falls within 2 standard deviations, and about 99.7% falls within 3 standard deviations.
Question 9: A study has a sample size of 15. The researcher is testing the
hypothesis that the sample mean is different from a known population mean.
Which test should be used, assuming the population standard deviation is
unknown?
A. z-test
B. Paired t-test
C. One-sample t-test
D. Chi-square test
CORRECT ANSWER: C. One-sample t-test
Rationale: A one-sample t-test is used to compare the mean of a single sample to a
known population mean when the population standard deviation is unknown. It is
appropriate for smaller sample sizes (n < 30), as the t-distribution is used to account for
the extra uncertainty in estimating the standard deviation from the sample.
Question 10: A researcher is studying the correlation between hours of
exercise per week and resting heart rate. The calculated Pearson correlation
coefficient (r) is -0.85. What does this indicate?
A. A weak, positive linear relationship.
B. A strong, positive linear relationship.
C. A weak, negative linear relationship.
D. A strong, negative linear relationship.
CORRECT ANSWER: D. A strong, negative linear relationship.
Rationale: The Pearson correlation coefficient (r) ranges from -1 to +1. A value of -0.85
indicates a strong linear relationship because the absolute value is close to 1. The
negative sign indicates an inverse relationship: as hours of exercise increase, resting
heart rate tends to decrease.
Question 11: A hospital calculates the sensitivity of a new diagnostic test for a
disease. Sensitivity is defined as the probability of:
A. A negative test result given the patient does not have the disease.
B. A positive test result given the patient does not have the disease.
