How should a nurse researcher expect a sample to differ from a population?

Choice A rationale

The results section is dedicated to the objective presentation of findings without interpretation or commentary. It utilizes descriptive and inferential statistics to summarize data collected during the investigation. Scientists use this area to report numerical values, p-values, and correlation coefficients. Because its purpose is strictly limited to what was observed, it does not provide the analytical space required to critique the study's own internal or external validity limitations or procedural weaknesses.

Choice B rationale

The methods section details the specific blueprint and operational steps taken to conduct the research. It covers the population, sampling techniques, instrumentation, and data collection protocols. While it explains how the study was executed, it serves as a descriptive manual rather than a self-reflective critique. It provides the context necessary for replication but does not offer the evaluative commentary needed to address how specific methodological choices might have constrained the final outcomes or generalizability.

Choice C rationale

The discussion section provides the researcher with a platform to interpret findings, compare them with existing literature, and acknowledge study limitations. This is where the scientist candidly addresses factors like small sample sizes, potential biases, or uncontrolled variables that may have influenced the results. By evaluating these weaknesses, the researcher assists the scientific community in understanding the boundaries of the data. This critical self-appraisal is essential for contextualizing the study's contribution to nursing knowledge.

Choice D rationale

The literature review establishes the theoretical framework and summarizes existing knowledge regarding the research problem. It identifies gaps in previous studies to justify the need for the current investigation. While it critiques the weaknesses of prior research, it does not serve as a venue for discussing the limitations of the new study being reported. Its primary function is to synthesize historical and contemporary evidence to provide a comprehensive background for the researcher's specific hypothesis.

Choice A rationale

Quasi-experimental designs are often chosen when true experimental control is impossible or unethical in clinical environments. These designs allow researchers to study interventions in real-world settings where random assignment might not be feasible. By conducting research in naturalistic environments, findings may have higher ecological validity compared to strictly controlled laboratory settings. This flexibility is essential for nursing research conducted in busy hospital units where maintaining a strictly controlled experimental group is often practically difficult.

Choice B rationale

Sample size requirements are generally determined by power analysis rather than the specific choice between experimental or quasi-experimental designs. While quasi-experiments are useful when participant numbers are limited, they actually often require larger samples to compensate for the lack of randomization and potential confounding variables. Therefore, the preference for a quasi-experimental design is rarely based on the sufficiency of a smaller sample size, as statistical significance still depends on the effect size.

Choice C rationale

Descriptive statistics are used across all types of research designs to summarize demographic data and basic characteristics of the sample. They are not a primary reason to select a quasi-experimental design over a true experiment. Both designs rely heavily on inferential statistics to test for differences between groups or changes over time. Choosing a design based solely on the use of descriptive statistics would overlook the primary goal of quasi-experiments, which is evaluating interventions.

Choice D rationale

True experimental designs remain the gold standard for establishing cause-and-effect relationships because they involve randomization, control groups, and manipulation of the independent variable. Quasi-experimental designs are weaker in this regard because they lack random assignment, which increases the risk of internal validity threats. If the primary desired outcome is the definitive demonstration of causality, a true experimental design would be preferred over a quasi-experimental one whenever the study conditions allow.