WGU D514 Analytical Methods of Healthcare
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Terms in this set (134)
ANOVA test Analysis of variance (ANOVA) may be used in
research studies where there are two or more
groups to compare.
Chi-square tests Chi-square tests determine if an association
exists between two categorical variables.
Control group In a healthcare environment, this group of
patients does not receive the treatment that is
being studied.
Experimental group This group of patients receives the treatment
being studied with follow-up observation to
determine the effect of the treatment.
,F-test 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 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 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 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 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 Mean is the arithmetic average. Divide the sum of
all scores by the total number of scores.
Median 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 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 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 Mode is the value that occurs most frequently in
the data.
Multivariate regression analyses 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 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 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."
Leaders Exam |(Latest 2026 Update) Complete
Questions and Guide Answers, 100% Verified
Graded A+
Save
Terms in this set (134)
ANOVA test Analysis of variance (ANOVA) may be used in
research studies where there are two or more
groups to compare.
Chi-square tests Chi-square tests determine if an association
exists between two categorical variables.
Control group In a healthcare environment, this group of
patients does not receive the treatment that is
being studied.
Experimental group This group of patients receives the treatment
being studied with follow-up observation to
determine the effect of the treatment.
,F-test 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 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 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 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 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 Mean is the arithmetic average. Divide the sum of
all scores by the total number of scores.
Median 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 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 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 Mode is the value that occurs most frequently in
the data.
Multivariate regression analyses 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 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 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."
