What is essential for minimizing the chance of biased outcomes in research?

Establishing a data selection strategy before data collection is crucial for minimizing the chance of biased outcomes in research. This proactive approach ensures that researchers outline clear criteria for including or excluding data, which helps maintain objectivity throughout the study. By defining the selection criteria in advance, researchers can avoid tendencies to manipulate or selectively report data based on findings that align with preconceived notions or hypotheses.

This strategy also contributes to the reliability and validity of the research results, as it promotes systematic and consistent data collection methods that align with the study's objectives. When a solid data selection strategy is in place, the risk of introducing biases related to participant selection, data measurement, or the interpretation of results significantly diminishes, ultimately strengthening the integrity of the research process.