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Module three study worksheet.

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Module three study worksheet. Module three study worksheet. Module three study worksheet.

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Module Three Study Worksheet.
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Module three study worksheet.

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1




Instructions to the student: The reading worksheets are designed to assist you as you review the
assigned readings in your Grove, Gray, and Burns (2015) textbook for this module. Read the assigned
pages below, and answer the following questions.



Chapter Nine: Examining Populations and Samples in
Research

Samples, samples, samples! If you don’t understand the way researchers get their subjects, how will you
know if you can generalize the results to your area or unit? Chapter Nine will help you to unlock the
secrets of examining populations and samples in the research articles you are reading so that they will
make more sense to you.


• What is the difference between sample, sampling, and sampling plan or sampling method?
o Sampling Plan/Method - a sampling plan or sampling method outlines the strategies
used to obtain samples for studies. There are two major types of sampling plans:
probability and non-probability.
o Sample - The sample defines the selected group of people (or elements).
o Sampling – Process of selecting participants who are representative of the population
being studied.
• Define the following terms: population, target population, and accessible population.
o Population - The population is a particular group of individuals or elements (such as a
group of people with Type II Diabetes) who are the focus of the research.
o Target Population - The target population is a group of individuals who meet a
particular set of sampling criteria, such as: female, 18 years or older, new diagnosis of
type II diabetes, not on insulin.

o Accessible population - The portion of the target population to which the researcher
has reasonable access. The accessible population might include elements within a
country, state, city, hospital, nursing unit, or primary care clinic...such as the diabetics
in a primary care clinic in Arlington, TX.


What is an element?



©2015 UTA School of Nursing 1

, 2


The individual units of the population and sample are called elements. An element can
be a person, event, behavior, or any other single unit of study.



Remember: when elements are persons, they can be called subjects or participants
depending on the research design.


o

• Qualitative studies call the people who participate in them participants; quantitative studies are
more likely to identify them as subjects.




©2015 UTA School of Nursing 2

, 3


• What is generalization and why is it important?

o Generalization extends the findings from the sample under study to the larger
population. The quality of the study and the consistency of the study's findings with
the findings from previous research in this area influence the extent of the
generalization.


• Your book explains the concept of sampling or eligibility criteria. What are inclusion and
exclusion sampling criteria? Why is it important to understand these in a research study that you
are reviewing?
o inclusion sampling criteria - the characteristics that the subject or element must
possess to be a part of the target population.

o exclusion sampling criteria - the characteristics that can cause a person or element to
be excluded from the target population.
o sampling criteria - A list of characteristics essential for eligibility or membership in the
target population.

• Describe representativeness of a sample –
• means that the sample, the accessible population, and the target population are alike in as
many ways as possible. In quantitative research, you need to evaluate representativeness in
terms of the setting, characteristics of the subjects, and the distribution of values on variables
measured in the study.
• What is the difference between random variation and systematic variation in a subject’s values?
If you were a nurse researcher, which one of these do you think you would like to avoid in your
study if possible (because it introduces bias)?

o Random variation - The expected difference in values that occurs when different
subjects from the same sample are examined.
▪ The difference is random because some subjects will score higher and others
will be lower than the average (mean) population value. (Think: IQ scores...we
don't all have the same IQ.)
▪ As the sample size increases, random variation decreases, improving
representativeness of the results.

o Systematic variation - A consequence of selecting subjects whose measurement values
differ in some specific way from those of the general population. (Think: A study about
attitudes about health behaviors. What if we only ask nurses? They may view this
differently than if we just took a sample of adults from the general population.)
▪ Because these subjects have something in common, their values tend to be
similar to others in the sample, but different from the values that might be
achieved in the general population. This can introduce bias into the results.
©2015 UTA School of Nursing 3

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