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