Final answer:
Redundant or irrelevant data is often gathered due to the reduction in the cost of data collection, inadequate research methodologies, and bias. The choice of research method heavily influences data relevance, and a clear justification for the selection of data types is necessary for meaningful research outcomes.
Step-by-step explanation:
Factors such as the reduction in the cost of data collection often lead to the accumulation of redundant or irrelevant data. The ease and affordability of collecting data can result in vast amounts of information, not all of which is pertinent or necessary for a particular research goal. Moreover, there are specific concerns about the collection process itself. When considering research techniques such as surveys or observational studies, each has its limitations. Surveys may suffer from the constraints of self-reported data and may not always capture the depth needed for certain research questions. On the other hand, while observational studies provide a wealth of information, they can be too specific, limiting their applicability to the wider population. Archival research may involve using data collected with different aims and methodologies, which may not align with the current study's objectives. Complications such as these can result in a greater volume of data that includes extraneous material not relevant to the current hypothesis or research question.
Bias can also play a role, either through selective omission or by stopping data collection prematurely once preliminary results support the hypothesis, potentially ignoring additional data that could contradict initial findings. This methodological myopia can greatly affect the validity and reliability of the study and lead to an accumulation of irrelevant or redundant data, which does not contribute to a meaningful understanding of the subject under investigation.
Finally, researchers must also justify the selection of data types that are aligned with their scientific questions, as per AP guidelines 4.1. Without a clear justification for the data chosen, research can be steered in an unproductive direction filled with redundancy and irrelevance.