2025/26 WGU D514 ANALYTICAL
METHODS OF HEALTHCARE LEADERS PRE-
TEST TERMS QUESTIONS & ANSWERS
ANOVA
Analysis of variance test. Used when there are two or more groups to
compare.
A group of psychiatric patients are trying three different therapies:
counseling, medication, and biofeedback. You want to see if one
therapy is better than others.
Alternative Hypothesis
States that the two groups we are studying are different: this is the
researcher's hypothesis, the alternative model that you want to
consider. The burden of proof lies with the researcher.
Analysis Plan
A data analysis plan is a roadmap for how you're going to organize and
analyze your survey data -- and it should help you achieve three
objectives that relate to the goal you set before you started your survey.
Bayesian Approach
an advanced mathematical procedure that applies probabilities to
statistical problems. It provides people the tools to update their beliefs
in the evidence of new data.
Categorical Variable
,Values that are names or labels. The color of a ball or the breed of a dog
would be examples of categorical variables.
Central Tendency
Is the phenomenon of typical values often occurring in the middle of a
distribution. The greater the tendency toward the center, the more
likely a distribution is normal in shape.
Chi-square Test
Determine if an association exists between two categorical variables.
Compares values you observe to expected.
Do men or women call out sick to work more?
Confounding Variable
A variable that obscures the effect of another variable.
Continuous Variable
It is also known as an interval variable. There is a meaningful difference
between variables. For example, a temperature difference between
80 and 90 is the same difference as between 90 and 100.
Congrol Group
In a healthcare environment, this group of patients do not receive the
treatment that is being studied.
Correlation Coefficient
Measures strength and direction of a linear relationship between 2
variables on a scatter plot.
, Looks for not only the relationship, but the magnitude of association. It
is not cause and effect, just relationship.
Cross-Sectional Research
Also called a prevalence study, it gathers and analyzes data from a
population or subset of a population at a specific point in time or place.
For example, a group of physicians may wish to do a cross-sectional
study to see how many of their patients ages 10-14 are on medication
for ADHD.
Dependent Variable
It is what is going to change, or not, as a result of your research.
For example, if you are researching whether or not exercising has an
effect on weight gain, 'exercise' is the independent variable and weight
gain is the dependent variable.
Descriptive Statistics
Describe what the data show about the characteristics of a sample --
they tell us information about a particular population. They are
considered accurate and can be verified.
Experimental Group
This group of patients receive the treatment being studied, and with
follow-up observation to determine the effect of the treatment.
F-test
For equality of variance: It is most often used when comparing
statistical models that have been fitted to a data set, to identify the
METHODS OF HEALTHCARE LEADERS PRE-
TEST TERMS QUESTIONS & ANSWERS
ANOVA
Analysis of variance test. Used when there are two or more groups to
compare.
A group of psychiatric patients are trying three different therapies:
counseling, medication, and biofeedback. You want to see if one
therapy is better than others.
Alternative Hypothesis
States that the two groups we are studying are different: this is the
researcher's hypothesis, the alternative model that you want to
consider. The burden of proof lies with the researcher.
Analysis Plan
A data analysis plan is a roadmap for how you're going to organize and
analyze your survey data -- and it should help you achieve three
objectives that relate to the goal you set before you started your survey.
Bayesian Approach
an advanced mathematical procedure that applies probabilities to
statistical problems. It provides people the tools to update their beliefs
in the evidence of new data.
Categorical Variable
,Values that are names or labels. The color of a ball or the breed of a dog
would be examples of categorical variables.
Central Tendency
Is the phenomenon of typical values often occurring in the middle of a
distribution. The greater the tendency toward the center, the more
likely a distribution is normal in shape.
Chi-square Test
Determine if an association exists between two categorical variables.
Compares values you observe to expected.
Do men or women call out sick to work more?
Confounding Variable
A variable that obscures the effect of another variable.
Continuous Variable
It is also known as an interval variable. There is a meaningful difference
between variables. For example, a temperature difference between
80 and 90 is the same difference as between 90 and 100.
Congrol Group
In a healthcare environment, this group of patients do not receive the
treatment that is being studied.
Correlation Coefficient
Measures strength and direction of a linear relationship between 2
variables on a scatter plot.
, Looks for not only the relationship, but the magnitude of association. It
is not cause and effect, just relationship.
Cross-Sectional Research
Also called a prevalence study, it gathers and analyzes data from a
population or subset of a population at a specific point in time or place.
For example, a group of physicians may wish to do a cross-sectional
study to see how many of their patients ages 10-14 are on medication
for ADHD.
Dependent Variable
It is what is going to change, or not, as a result of your research.
For example, if you are researching whether or not exercising has an
effect on weight gain, 'exercise' is the independent variable and weight
gain is the dependent variable.
Descriptive Statistics
Describe what the data show about the characteristics of a sample --
they tell us information about a particular population. They are
considered accurate and can be verified.
Experimental Group
This group of patients receive the treatment being studied, and with
follow-up observation to determine the effect of the treatment.
F-test
For equality of variance: It is most often used when comparing
statistical models that have been fitted to a data set, to identify the
