D514 Exam Study Guide with Correct Solutions
ANOVA - ✔✔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 - ✔✔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 - ✔✔this group of patients does not receive the treatment that is being
studied
Experimental Group - ✔✔This group 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.
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 - ✔✔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 - ✔✔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 - ✔✔The arithmetic average. Divide the sum of all scores by the total number of
scores.
Median - ✔✔The midpoint of the distribution of values, or the point above or below
which 50 % 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 components - ✔✔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 - ✔✔the value that occurs most frequently in the data. Think most
Multivariate regression analyses - ✔✔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 - ✔✔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)
ANOVA - ✔✔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 - ✔✔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 - ✔✔this group of patients does not receive the treatment that is being
studied
Experimental Group - ✔✔This group 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.
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 - ✔✔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 - ✔✔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 - ✔✔The arithmetic average. Divide the sum of all scores by the total number of
scores.
Median - ✔✔The midpoint of the distribution of values, or the point above or below
which 50 % 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 components - ✔✔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 - ✔✔the value that occurs most frequently in the data. Think most
Multivariate regression analyses - ✔✔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 - ✔✔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)
