EDAPT EVALUATING QUANTITATIVE DATA – EVIDENCE BASED

EDAPT EVALUATING QUANTITATIVE DATA – EVIDENCE BASED
Analysis of quantitative data provides quantifiable and easy-to-understand results for the researcher.
Quantitative data can be analyzed in various ways and is classified as descriptive or inferential based on the
aims of the study. The knowledge gained by evaluating descriptive data will be essential when learning how to
evaluate quantitative data. Evaluating quantitative data helps the researcher or reader determine if
interventions make a significant difference and should be applied to practice.
A researcher collecting quantitative data analysis uses statistical methods to complete which actions? Select
all that apply.
Quantitative data analysis uses statistical methods to describe, compare, and summarize data.
A nurse is reviewing evidence-based research studies on how to reduce falls. Before implementing the
recommendations in nursing practice, the nurse should evaluate which factors from the study? Select all
that apply.
Size of the effect
Probability of error
Certainty of estimates
Statistical and clinical significance
Appropriateness of the test selected
The nurse understands the initial part of the results section of a study should provide DESCRIPTIVE statistics
about the SAMPLE and each VARIABLE for the nurse to gain a good understanding of the details of the
SAMPLE utilized in the study.
The nurse understands the initial part of the results section of a study should provide descriptive statistics
about the sample and each variable for the nurse to gain a good understanding of the details of the sample
utilized in the study. By doing so, the nurse will be able to grasp how the subjects responded to the
intervention and can generalize the results of the study to other groups.
COMMON ELEMENTS IN QUANTITATIVE ANALYSIS
DATA COLLECTION
Tools and methodologies that generate numbers. Examples of collection methods include: surveys
(questionnaires), structured observations, pilot studies, checklists, or direct measurements.
DATA STORAGE
Raw data is stored manually or electronically for retrieval when needed.
DATA ENTRY
Raw data is placed into a dataset and structured based on needs