NR 449- QUIZ 5 EXAM QUESTIONS AND
ANSWERS 100% PASS 2026 EDITION
What is inferential analysis - ANS •Statistical tests to determine if results found in a sample
are representative of a larger population.
•Inferential analysis is undertaken to determine if a specific result can be expected to occur in a
larger population, given that it was observed in a sample.
•In statistics, a sample (part of the population) is used to represent a target population (all of
the population); the question then becomes whether the same results found in the sample
would be found in the larger target population.
•Quantitative research as evidence for practice is useful only when it can be generalized to
larger groups of patients than those who were directly studied in the experiment. Inferential
analysis allows the nurse to recommend that an intervention be used and to do so with an
identified level of confidence that it is evidence based.
Applicability and transferability - ANS •The feasibility of applying qualitative research findings
to other samples and other settings.
•Replicability: - ANS •The likelihood that qualitative research outcomes or events will happen
again given the same circumstances.
What is descriptive data? - ANS •Descriptive data:
•Numbers in a data set that are collected to represent research variables.
1
@2026 EDITION ALLRIGHTS RESERVED
, •When it comes to descriptive analysis, those persons evaluating research as evidence have
different needs than do those persons who conduct the research studies. The purposes of
summarizing descriptive data for readers of research include:
•Giving the reader a quick grasp of the characteristics of the sample and the variables in the
study to understand its appropriate application as evidence
•Providing basic information on how variables in a study are alike (measures of central
tendency) and how they are different (measures of variability)
•Conveying information about the study through numerical and graphical methods to enhance
understanding of the findings (Scott & Mazhindu, 2014)
•The purposes of summarizing descriptive data for researchers include the following:
•Reviewing the data set using frequency tables to check for coding or data entry errors
•Visualizing the descriptive data—particularly the shape of distributions—to determine
whether statistical assumptions are met for the selection of appropriate statistical analysis
•Understanding the characteristics of the participants in the study and their performance on
variables of interest in the study
•Gaining an in-depth understanding of the data before inferential analysis
•Nominal-level data - ANS •Are those that denote categories and have no rank order;
numbers given to these data are strictly for showing membership in a category and are not
subject to mathematical calculations. Nominal data can be counted, but are not measured, so
they can be summarized using statistics that represent counts. Summary statistics appropriate
for this level of measurement are frequency, percentage, rates, ratios, and mode.
•Ordinal data are - ANS •Categories but have an added characteristic of rank order.
•These data differ from nominal data in that the categories for a variable can be identified as
being less than or greater than one another.
•However, because the level of measure is still categorical, the exact level of difference cannot
be identified. A pain scale, in spite of its representation as a series of numbers, is an example of
ordinal data. For example, while we know a score of 7 on this scale is greater than a 5, the
difference cannot be quantified.
2
@2026 EDITION ALLRIGHTS RESERVED
ANSWERS 100% PASS 2026 EDITION
What is inferential analysis - ANS •Statistical tests to determine if results found in a sample
are representative of a larger population.
•Inferential analysis is undertaken to determine if a specific result can be expected to occur in a
larger population, given that it was observed in a sample.
•In statistics, a sample (part of the population) is used to represent a target population (all of
the population); the question then becomes whether the same results found in the sample
would be found in the larger target population.
•Quantitative research as evidence for practice is useful only when it can be generalized to
larger groups of patients than those who were directly studied in the experiment. Inferential
analysis allows the nurse to recommend that an intervention be used and to do so with an
identified level of confidence that it is evidence based.
Applicability and transferability - ANS •The feasibility of applying qualitative research findings
to other samples and other settings.
•Replicability: - ANS •The likelihood that qualitative research outcomes or events will happen
again given the same circumstances.
What is descriptive data? - ANS •Descriptive data:
•Numbers in a data set that are collected to represent research variables.
1
@2026 EDITION ALLRIGHTS RESERVED
, •When it comes to descriptive analysis, those persons evaluating research as evidence have
different needs than do those persons who conduct the research studies. The purposes of
summarizing descriptive data for readers of research include:
•Giving the reader a quick grasp of the characteristics of the sample and the variables in the
study to understand its appropriate application as evidence
•Providing basic information on how variables in a study are alike (measures of central
tendency) and how they are different (measures of variability)
•Conveying information about the study through numerical and graphical methods to enhance
understanding of the findings (Scott & Mazhindu, 2014)
•The purposes of summarizing descriptive data for researchers include the following:
•Reviewing the data set using frequency tables to check for coding or data entry errors
•Visualizing the descriptive data—particularly the shape of distributions—to determine
whether statistical assumptions are met for the selection of appropriate statistical analysis
•Understanding the characteristics of the participants in the study and their performance on
variables of interest in the study
•Gaining an in-depth understanding of the data before inferential analysis
•Nominal-level data - ANS •Are those that denote categories and have no rank order;
numbers given to these data are strictly for showing membership in a category and are not
subject to mathematical calculations. Nominal data can be counted, but are not measured, so
they can be summarized using statistics that represent counts. Summary statistics appropriate
for this level of measurement are frequency, percentage, rates, ratios, and mode.
•Ordinal data are - ANS •Categories but have an added characteristic of rank order.
•These data differ from nominal data in that the categories for a variable can be identified as
being less than or greater than one another.
•However, because the level of measure is still categorical, the exact level of difference cannot
be identified. A pain scale, in spite of its representation as a series of numbers, is an example of
ordinal data. For example, while we know a score of 7 on this scale is greater than a 5, the
difference cannot be quantified.
2
@2026 EDITION ALLRIGHTS RESERVED
