NR-449: Evidence-Based Practice Verified
Practice Questions with A+ Answers | Final Exam
Guide FOR 2025/2026 (the most recent quizzes)
Sampling Strategy - The overall approach used to select a subset of individuals (a sample)
from a larger group (the population) to study.
Population - The entire group of individuals that the researcher is interested in
generalizing the findings to.
Sample - A subgroup of the population that is selected to participate in the research study.
Sampling Error - The difference between the characteristics of the sample and the
characteristics of the population from which it was drawn.
Qualitative Research Sampling - Focuses on in-depth understanding and often uses
purposeful selection of participants who can best inform the research question.
Quantitative Research Sampling - Aims for generalizability and often uses probability
(random) sampling methods to ensure each member of the population has a known chance of
being selected.
Selection Bias - Occurs when the process used to select participants or assign them to
groups is not impartial, leading to a sample that is not representative of the population and
threatening the study's validity.
Random Sampling - A method where every member of the available population has an
equal and independent chance of being selected for the sample.
Random Assignment - A procedure used in experimental designs where participants are
randomly assigned to different treatment groups to control for confounding variables.
Sampling Frame - A list of all the individuals within the population who are accessible to
the researcher.
Inclusion Criteria - Characteristics that individuals must possess to be eligible for
participation in a study.
Exclusion Criteria - Characteristics that disqualify individuals from participating in a
study.
Purposeful Sampling - A non-probability sampling technique used in qualitative research
where participants are selected based on specific characteristics relevant to the research question.
, Probability Sampling (Random Sampling) - Sampling techniques used in quantitative
research where every member of the population has a known and non-zero chance of being
selected.
Independence (in sampling) - Each subject's selection is an independent event, meaning
the selection of one subject does not influence the selection of others.
Nonindependent Designs - Study designs where observations are not independent, such as
pretest/posttest or time series designs, or when subjects are related.
Convenience Sampling - A non-probability sampling technique where participants are
selected based on their availability and willingness to participate.
Sampling Methods for Hard-to-Reach Populations - Strategies used to recruit individuals
who are difficult to access, such as using native language communication, experience sampling,
respondent-driven sampling, and service-based sampling.
Mixing Methods in Sampling - Combining different sampling techniques, often necessary
when studying rare phenomena, such as combining cluster and referral sampling.
Sample Size in Qualitative Research - Often determined by data saturation and
redundancy, rather than a predetermined number.
Sample Size in Quantitative Research - A function of the desired significance level,
statistical power, and the expected magnitude of the effect.
Type II Error - Failing to reject a false null hypothesis, often a concern with small sample
sizes in quantitative research.
External Validity - The extent to which the results of a study can be generalized to other
populations, settings, and times.
Internal Validity - The extent to which a study can demonstrate a causal relationship
between the independent and dependent variables, free from the influence of confounding
factors.
Measurement - The process of assigning numbers or classifications to characteristics or
attributes according to specific rules.
Conceptual Definition - A broad, abstract definition of a variable using other concepts.
Operational Definition - A precise description of how a variable will be measured in a
study, outlining the specific procedures or operations to be performed.
Primary Data - Data collected directly by the researcher from the participants for the
specific purpose of the research study.
Practice Questions with A+ Answers | Final Exam
Guide FOR 2025/2026 (the most recent quizzes)
Sampling Strategy - The overall approach used to select a subset of individuals (a sample)
from a larger group (the population) to study.
Population - The entire group of individuals that the researcher is interested in
generalizing the findings to.
Sample - A subgroup of the population that is selected to participate in the research study.
Sampling Error - The difference between the characteristics of the sample and the
characteristics of the population from which it was drawn.
Qualitative Research Sampling - Focuses on in-depth understanding and often uses
purposeful selection of participants who can best inform the research question.
Quantitative Research Sampling - Aims for generalizability and often uses probability
(random) sampling methods to ensure each member of the population has a known chance of
being selected.
Selection Bias - Occurs when the process used to select participants or assign them to
groups is not impartial, leading to a sample that is not representative of the population and
threatening the study's validity.
Random Sampling - A method where every member of the available population has an
equal and independent chance of being selected for the sample.
Random Assignment - A procedure used in experimental designs where participants are
randomly assigned to different treatment groups to control for confounding variables.
Sampling Frame - A list of all the individuals within the population who are accessible to
the researcher.
Inclusion Criteria - Characteristics that individuals must possess to be eligible for
participation in a study.
Exclusion Criteria - Characteristics that disqualify individuals from participating in a
study.
Purposeful Sampling - A non-probability sampling technique used in qualitative research
where participants are selected based on specific characteristics relevant to the research question.
, Probability Sampling (Random Sampling) - Sampling techniques used in quantitative
research where every member of the population has a known and non-zero chance of being
selected.
Independence (in sampling) - Each subject's selection is an independent event, meaning
the selection of one subject does not influence the selection of others.
Nonindependent Designs - Study designs where observations are not independent, such as
pretest/posttest or time series designs, or when subjects are related.
Convenience Sampling - A non-probability sampling technique where participants are
selected based on their availability and willingness to participate.
Sampling Methods for Hard-to-Reach Populations - Strategies used to recruit individuals
who are difficult to access, such as using native language communication, experience sampling,
respondent-driven sampling, and service-based sampling.
Mixing Methods in Sampling - Combining different sampling techniques, often necessary
when studying rare phenomena, such as combining cluster and referral sampling.
Sample Size in Qualitative Research - Often determined by data saturation and
redundancy, rather than a predetermined number.
Sample Size in Quantitative Research - A function of the desired significance level,
statistical power, and the expected magnitude of the effect.
Type II Error - Failing to reject a false null hypothesis, often a concern with small sample
sizes in quantitative research.
External Validity - The extent to which the results of a study can be generalized to other
populations, settings, and times.
Internal Validity - The extent to which a study can demonstrate a causal relationship
between the independent and dependent variables, free from the influence of confounding
factors.
Measurement - The process of assigning numbers or classifications to characteristics or
attributes according to specific rules.
Conceptual Definition - A broad, abstract definition of a variable using other concepts.
Operational Definition - A precise description of how a variable will be measured in a
study, outlining the specific procedures or operations to be performed.
Primary Data - Data collected directly by the researcher from the participants for the
specific purpose of the research study.
