WGU D514 EXAM STUDY GUIDE
ANOVA - Answers - Analysis of variance (ANOVA) may be used in research studies
where there are three or more groups to compare.
Stands for analysis of variance. The ANOVA test is similar to the independent-samples
t-test. It is used as a test to compare means between independent variables with similar
variance and normality of distribution. Whereas the t-test compares just two means, an
ANOVA test can be used to compare multiple groups.
Example: Researchers are performing a randomized clinical trial evaluating the
effectiveness of three distinct treatments for painful TMJ clicking.
60 patients were randomly assigned to 3 treatment options: (A) anterior positioning
splint therapy; (B) physical therapy; (C) physical therapy and splinting.
Similar to the t-test in that patients are all from same type of distribution (they have the
same medical diagnosis) but there are more than 2 treatments in the experimental
study.
Chi-Square Test - Answers - Determines if an association exists between two
categorical variables. Qualitative in nature.
Tests for relationships between categorical variables. Chi Square is used when you are
comparing values you can observe with those you expect.
• Chi square is a group of tests generally used with qualitative or non-normal data.
There are chi-square tests that can be used to compare independent measures as well
as tests to look for differences or for relationships
Example: The owner of a laboratory wants to keep sick leave as low as possible by
keeping employees healthy through disease prevention programs. Many employees get
flu in the winter months, leading to productivity problems due to sick leave from the
disease. There are many sources for flu vaccine today, and the owner believes that it is
important to get as many employees vaccinated as possible. Due to a regional
shortage, there was only enough vaccine for half the employees, last flu season. In
effect, there are two groups; employees who received the vaccine and employees who
did not receive the vaccine. The company sent a nurse to every employee who calls in
sick with flu, to provide care if needed, and provide a nursing assessment. They kept
track of the number of employees who contracted flu and the severity of symptoms.
Control Group - Answers - this group of patients does not receive the treatment that is
being studied
Experimental Group - Answers - This group receives the treatment being studied with
follow-up observation to determine the effect of the treatment.
F-test - Answers - 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.
For equality of variance: It is most often used when comparing statistical models that
have been fitted to a data set, to identify the model that best fits the population from
which the data were sampled. Ensuring two samples are 'not statistically different'.
,Two population variables are equal.
Rules for tests F, z and t: dependent variable must be measured on the interval scale;
samples must come from normally distributed population; for tests z and t, the variance
of the samples must be equal.
Frequency - Answers - 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 - Answers - 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 - Answers - 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 - Answers - 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 - Answers - The arithmetic average. Divide the sum of all scores by the total
number of scores.
Median - Answers - The midpoint of the distribution of values, or the point above or
below which 50 % of the values fall.
Methods section components - Answers - 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 components - Answers - Interpreting and presenting the results of
data analysis affords many opportunities for accidental or deliberate misrepresentation
of the data. Common examples include implying causation, extrapolating beyond the
reasonable, relying on a biased or incomplete sample, and using inappropriate
graphical representations.
Mode - Answers - the value that occurs most frequently in the data. Think most
Multivariate regression analyses - Answers - Can be used to analyze and adjust risk.
This analysis model contrasts each measured factor to the patients risk of a particular
outcome.
, Nominal data - Answers - Can be measured as a frequency or percentage, and the
mean of these data cannot be calculated. Nominal data in healthcare might include
demographic data about patients. The work nominal means "pertaining to name"
Names (category)
Nominal Data: various cancer types; different insurance companies; physician
specialties offered at a clinic; types of medical units in a hospital (ICU, pediatrics, med-
surg)
Ordinal Data - Answers - 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"
Ordinal Data: data found in a Likert scale; pain scale; stages of cancer; trimesters of
pregnancy.
Ordinal Variable is a type of variable where the order or ranking of values matters, but
the differences between values may not be uniform. In ordinal variables, the intervals
between values are not consistent. An example is a pain scale where the order of pain
severity matters, but the difference between a rank of "7" and "5" may not be the same
as between "5" and "3".
Parametric Tests - Answers - Based on probability distribution.
Statistical tests that make assumptions about the parameters of the population
distribution(s) from which the data are drawn. These tests are based on specific
distributional assumptions and are used in inferential statistics. Parametric tests are
sensitive to the underlying distribution of data and are applicable when certain
conditions are met.
Parametric: summarizes a population (the entire group you are interested in
investigating)
Using a t-test to compare the means of two groups when the data are assumed to follow
a normal distribution.
Nonparametric tests - Answers - Used when data are not normally distributed.
Statistical tests that make no assumptions about the parameters of the population
distribution(s) from which the data are drawn. Also known as distribution-free tests, non-
parametric tests do not rely on specific distributional assumptions and are considered
more robust when dealing with non-normally distributed data or ordinal variables. These
tests are suitable when the requirements for parametric tests cannot be met.
Example: Employing the Wilcoxon rank-sum test to compare the medians of two
independent groups when the assumption of normality is questionable.
Pearson's Correlation - Answers - is used with the interval and ordinal scale data and
determines the extent to which a change in one variable tends to be associated with a
change in another.
aka correlation coefficient
As people age, their likelihood of having arthritic changes increases. (positive
correlation)
As people increase their exercise activity, their weight decreases. (negative correlation)
ANOVA - Answers - Analysis of variance (ANOVA) may be used in research studies
where there are three or more groups to compare.
Stands for analysis of variance. The ANOVA test is similar to the independent-samples
t-test. It is used as a test to compare means between independent variables with similar
variance and normality of distribution. Whereas the t-test compares just two means, an
ANOVA test can be used to compare multiple groups.
Example: Researchers are performing a randomized clinical trial evaluating the
effectiveness of three distinct treatments for painful TMJ clicking.
60 patients were randomly assigned to 3 treatment options: (A) anterior positioning
splint therapy; (B) physical therapy; (C) physical therapy and splinting.
Similar to the t-test in that patients are all from same type of distribution (they have the
same medical diagnosis) but there are more than 2 treatments in the experimental
study.
Chi-Square Test - Answers - Determines if an association exists between two
categorical variables. Qualitative in nature.
Tests for relationships between categorical variables. Chi Square is used when you are
comparing values you can observe with those you expect.
• Chi square is a group of tests generally used with qualitative or non-normal data.
There are chi-square tests that can be used to compare independent measures as well
as tests to look for differences or for relationships
Example: The owner of a laboratory wants to keep sick leave as low as possible by
keeping employees healthy through disease prevention programs. Many employees get
flu in the winter months, leading to productivity problems due to sick leave from the
disease. There are many sources for flu vaccine today, and the owner believes that it is
important to get as many employees vaccinated as possible. Due to a regional
shortage, there was only enough vaccine for half the employees, last flu season. In
effect, there are two groups; employees who received the vaccine and employees who
did not receive the vaccine. The company sent a nurse to every employee who calls in
sick with flu, to provide care if needed, and provide a nursing assessment. They kept
track of the number of employees who contracted flu and the severity of symptoms.
Control Group - Answers - this group of patients does not receive the treatment that is
being studied
Experimental Group - Answers - This group receives the treatment being studied with
follow-up observation to determine the effect of the treatment.
F-test - Answers - 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.
For equality of variance: It is most often used when comparing statistical models that
have been fitted to a data set, to identify the model that best fits the population from
which the data were sampled. Ensuring two samples are 'not statistically different'.
,Two population variables are equal.
Rules for tests F, z and t: dependent variable must be measured on the interval scale;
samples must come from normally distributed population; for tests z and t, the variance
of the samples must be equal.
Frequency - Answers - 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 - Answers - 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 - Answers - 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 - Answers - 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 - Answers - The arithmetic average. Divide the sum of all scores by the total
number of scores.
Median - Answers - The midpoint of the distribution of values, or the point above or
below which 50 % of the values fall.
Methods section components - Answers - 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 components - Answers - Interpreting and presenting the results of
data analysis affords many opportunities for accidental or deliberate misrepresentation
of the data. Common examples include implying causation, extrapolating beyond the
reasonable, relying on a biased or incomplete sample, and using inappropriate
graphical representations.
Mode - Answers - the value that occurs most frequently in the data. Think most
Multivariate regression analyses - Answers - Can be used to analyze and adjust risk.
This analysis model contrasts each measured factor to the patients risk of a particular
outcome.
, Nominal data - Answers - Can be measured as a frequency or percentage, and the
mean of these data cannot be calculated. Nominal data in healthcare might include
demographic data about patients. The work nominal means "pertaining to name"
Names (category)
Nominal Data: various cancer types; different insurance companies; physician
specialties offered at a clinic; types of medical units in a hospital (ICU, pediatrics, med-
surg)
Ordinal Data - Answers - 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"
Ordinal Data: data found in a Likert scale; pain scale; stages of cancer; trimesters of
pregnancy.
Ordinal Variable is a type of variable where the order or ranking of values matters, but
the differences between values may not be uniform. In ordinal variables, the intervals
between values are not consistent. An example is a pain scale where the order of pain
severity matters, but the difference between a rank of "7" and "5" may not be the same
as between "5" and "3".
Parametric Tests - Answers - Based on probability distribution.
Statistical tests that make assumptions about the parameters of the population
distribution(s) from which the data are drawn. These tests are based on specific
distributional assumptions and are used in inferential statistics. Parametric tests are
sensitive to the underlying distribution of data and are applicable when certain
conditions are met.
Parametric: summarizes a population (the entire group you are interested in
investigating)
Using a t-test to compare the means of two groups when the data are assumed to follow
a normal distribution.
Nonparametric tests - Answers - Used when data are not normally distributed.
Statistical tests that make no assumptions about the parameters of the population
distribution(s) from which the data are drawn. Also known as distribution-free tests, non-
parametric tests do not rely on specific distributional assumptions and are considered
more robust when dealing with non-normally distributed data or ordinal variables. These
tests are suitable when the requirements for parametric tests cannot be met.
Example: Employing the Wilcoxon rank-sum test to compare the medians of two
independent groups when the assumption of normality is questionable.
Pearson's Correlation - Answers - is used with the interval and ordinal scale data and
determines the extent to which a change in one variable tends to be associated with a
change in another.
aka correlation coefficient
As people age, their likelihood of having arthritic changes increases. (positive
correlation)
As people increase their exercise activity, their weight decreases. (negative correlation)
