HEALTH CARE LEADERS TEST 4 2026 FULL
QUESTION COLLECTION EVIDENCE BASED
LEADERSHIP DECISION MAKING GUIDE
◉ Chi-square tests.
Answer: Chi-square tests determine if an association exists between
two categorical variables.
◉ Control group.
Answer: In a healthcare environment, this group of patients does not
receive the treatment that is being studied.
◉ Experimental group.
Answer: This group of patients receives the treatment being studied
with follow-up observation to determine the effect of the treatment.
◉ F-test.
Answer: The F-test is designed to test if two population variances
are equal. The ratio of the two variances is compared. If they are
equal, the ratio of the variances will be 1.
,◉ Frequency.
Answer: Frequencies measure how often a particular value occurs to
assess the importance of a value or check the variation of the values
in a study.
◉ Hypothesis.
Answer: A proposed explanation for an observation that leads to a
prediction. Through investigation and the use of statistical data,
those doing the study will either confirm or reject the hypothesis.
Testing the hypothesis will show if there is a link (or not) between
two or more variables.
◉ Integrity.
Answer: Research always makes some assumptions, depending on
the type of method used. Research assumptions must be identified
to determine possible breaches of integrity.
◉ Interval data.
Answer: Interval data includes units of equal size, such as IQ results.
There is no zero point. An example of interval scale is time: Time is
measured in 24 hours in each day; the time between each hour is the
same, 60 minutes.
◉ Mean.
,Answer: Mean is the arithmetic average. Divide the sum of all scores
by the total number of scores.
◉ Median.
Answer: Median is the midpoint of the distribution of values, or the
point above or below which 50 percent of the values fall.
◉ Methods section components.
Answer: When analyzing the quality of a study, a careful evaluation
of the research methods can reveal critical details about population
and sample, covariables and hypothesis, data presentation,
statistical analysis, and study limitations.
◉ Misleading statistics.
Answer: Interpreting and presenting the results of data analysis
affords many opportunities for accidental or deliberate
misrepresentations of data. Common examples include implying
causation, extrapolating beyond the reasonable, relying on a biased
or incomplete sample, and using inappropriate graphical
representations.
◉ Mode.
Answer: Mode is the value that occurs most frequently in the data.
, ◉ Multivariate regression analyses.
Answer: Multivariate regression analyses can be used to analyze and
adjust risk. This analysis model contrasts each measured factor to
the patient's risk of a particular outcome.
◉ Nominal data.
Answer: Nominal data can be measured as a frequency or
percentage, and the mean of these data cannot be calculated.
Nominal data in healthcare might include demographic information
about patients. The word nominal means "pertaining to a name."
◉ Ordinal data.
Answer: Ordinal data can be measured as a frequency, and the mean
of ordinal data is often calculated. Ordinal data in healthcare might
include patient satisfaction surveys using a Likert scale. The word
ordinal means to "put in order."
◉ Parametric and nonparametric tests.
Answer: Parametric tests are based on probability distributions.
Nonparametric tests are used when data are not normally
distributed.
◉ Pearson's correlation.