NR 449 Exam Questions and Answers latest
Update | 100% Correct
What is inferential analysis - ✅✅•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 - ✅✅•The feasibility of applying qualitative
research findings to other samples and other settings.
•Replicability: - ✅✅•The likelihood that qualitative research outcomes or
events will happen again given the same circumstances.
What is descriptive data? - ✅✅•Descriptive data:
•Numbers in a data set that are collected to represent research variables.
•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 - ✅✅•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 - ✅✅•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.
Update | 100% Correct
What is inferential analysis - ✅✅•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 - ✅✅•The feasibility of applying qualitative
research findings to other samples and other settings.
•Replicability: - ✅✅•The likelihood that qualitative research outcomes or
events will happen again given the same circumstances.
What is descriptive data? - ✅✅•Descriptive data:
•Numbers in a data set that are collected to represent research variables.
•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 - ✅✅•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 - ✅✅•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.
