WGU D514 HEALTHCARE LEADERS CORRECT
FINALS QUESTIONS AND ANSWERS SET A+
✔✔Confounding Variables - ✔✔May obscure the effect of the variables in the data.
They are often uncontrollable by the researcher.
✔✔Continuous Variable - ✔✔Meaningful difference between values
✔✔Dichotomous Variable - ✔✔Occurs in two possible states. For example; diabetic or
non-diabetic
✔✔Randomized Control Trial - ✔✔A scientific study design in which individuals are
randomly assigned to receive one of several clinical interventions. The interventions
include the experimental treatments and a control, which can be standard practice,
placebo, or no intervention at all. Helps minimize bias and ensured that any observed
effects are likely due to the treatment rather than the other
✔✔Demographic Statistic - ✔✔Looking at a specific population or group. Example;
women between 40-50 who live in Shelby, Montana
✔✔Focus Group - ✔✔A demographically diverse group of people assembled to
participate in a guided discussion about particular products or processes.
✔✔Case Study - ✔✔A type of non-participant observation in which researchers
investigate one person, one group, or one institution in depth.
✔✔The p-value - ✔✔Helps to assess whether differences between the observed value
and expected value represent chance
✔✔P-Value - ✔✔Level of probability. The lower the value, the less probable the results
occurred by chance.
, ✔✔Null hypothesis - ✔✔Two groups being studied that are the same. It serves as the
default assumption to be tested against the alternative hypothesis
✔✔Alternative Hypothesis - ✔✔Asserts that the two groups being studied are different.
It is the researcher's hypothesis, representing this model under consideration.
✔✔Sensitivity Analysis - ✔✔The examination of how uncertainties in the output of a
mathematical model or system can be attributed to various sources of uncertainty in its
inputs.
✔✔Sensitivity Analysis - ✔✔Examples of this is: When used in clinical trials, it is the
increasing of a dose of a new drug in a small increment, to look for changes and
strengthen any conclusions
✔✔Factor Analysis - ✔✔Process in which the values of observed data are expressed as
functions of a number of possible causes in order to find which are the most important.
✔✔Risk Stratification - ✔✔Used to classify patients into level of risk
✔✔Stratification Analysis - ✔✔The process of dividing a population into homogenous
subgroups before sampling. Allows for the examination of specific characteristics within
each subgroup, providing more nuanced insights into the overall population
✔✔Cross Sectional Research - ✔✔Type of observational study. Analyzes data collected
from a population or subset, at a specific time and point.
✔✔Pre and Post Test - ✔✔Test before and after an intervention
✔✔Time Series Analysis - ✔✔Methods for analyzing time series data in order to extract
meaningful statistics and other data characteristics.
✔✔Longitudinal Study - ✔✔Involves repeated observations of the same variables over
long periods of time.
✔✔Regression Analysis - ✔✔A statistical process used to estimate relationships among
variables. It involves modeling and analyzing multiple variables, especially the
relationship between a dependent and independent. Can include multiple predictors
simultaneously to assess their combined impact on the dependent variable.
✔✔Predictive Modeling - ✔✔A process used to identify patterns in data that can be
leveraged to predict the likelihood of a particular outcome. Involves using current data to
make forecasts about future events.
✔✔Cohort Study - ✔✔Establishing Links between risk factors and health outcomes.
FINALS QUESTIONS AND ANSWERS SET A+
✔✔Confounding Variables - ✔✔May obscure the effect of the variables in the data.
They are often uncontrollable by the researcher.
✔✔Continuous Variable - ✔✔Meaningful difference between values
✔✔Dichotomous Variable - ✔✔Occurs in two possible states. For example; diabetic or
non-diabetic
✔✔Randomized Control Trial - ✔✔A scientific study design in which individuals are
randomly assigned to receive one of several clinical interventions. The interventions
include the experimental treatments and a control, which can be standard practice,
placebo, or no intervention at all. Helps minimize bias and ensured that any observed
effects are likely due to the treatment rather than the other
✔✔Demographic Statistic - ✔✔Looking at a specific population or group. Example;
women between 40-50 who live in Shelby, Montana
✔✔Focus Group - ✔✔A demographically diverse group of people assembled to
participate in a guided discussion about particular products or processes.
✔✔Case Study - ✔✔A type of non-participant observation in which researchers
investigate one person, one group, or one institution in depth.
✔✔The p-value - ✔✔Helps to assess whether differences between the observed value
and expected value represent chance
✔✔P-Value - ✔✔Level of probability. The lower the value, the less probable the results
occurred by chance.
, ✔✔Null hypothesis - ✔✔Two groups being studied that are the same. It serves as the
default assumption to be tested against the alternative hypothesis
✔✔Alternative Hypothesis - ✔✔Asserts that the two groups being studied are different.
It is the researcher's hypothesis, representing this model under consideration.
✔✔Sensitivity Analysis - ✔✔The examination of how uncertainties in the output of a
mathematical model or system can be attributed to various sources of uncertainty in its
inputs.
✔✔Sensitivity Analysis - ✔✔Examples of this is: When used in clinical trials, it is the
increasing of a dose of a new drug in a small increment, to look for changes and
strengthen any conclusions
✔✔Factor Analysis - ✔✔Process in which the values of observed data are expressed as
functions of a number of possible causes in order to find which are the most important.
✔✔Risk Stratification - ✔✔Used to classify patients into level of risk
✔✔Stratification Analysis - ✔✔The process of dividing a population into homogenous
subgroups before sampling. Allows for the examination of specific characteristics within
each subgroup, providing more nuanced insights into the overall population
✔✔Cross Sectional Research - ✔✔Type of observational study. Analyzes data collected
from a population or subset, at a specific time and point.
✔✔Pre and Post Test - ✔✔Test before and after an intervention
✔✔Time Series Analysis - ✔✔Methods for analyzing time series data in order to extract
meaningful statistics and other data characteristics.
✔✔Longitudinal Study - ✔✔Involves repeated observations of the same variables over
long periods of time.
✔✔Regression Analysis - ✔✔A statistical process used to estimate relationships among
variables. It involves modeling and analyzing multiple variables, especially the
relationship between a dependent and independent. Can include multiple predictors
simultaneously to assess their combined impact on the dependent variable.
✔✔Predictive Modeling - ✔✔A process used to identify patterns in data that can be
leveraged to predict the likelihood of a particular outcome. Involves using current data to
make forecasts about future events.
✔✔Cohort Study - ✔✔Establishing Links between risk factors and health outcomes.
