A researcher collects a large number of data from several different experiments. She finds that not all data points support her hypothesis and so she excludes them from her final report.

What type of research misconduct is this describing?

Question

A researcher collects a large number of data from several different experiments.  She finds that not all data points support her hypothesis and so she excludes them from her final report.

What type of research misconduct is this describing?

BlackTom AI · Accepted Answer

The question describes a researcher who collects data from multiple experiments and then excludes certain data points because they do not support the hypothesis.

Because the researcher is manipulating the dataset by removing data that contradicts the desired conclusion, this action constitutes data falsification, a form of research misconduct where data are inappropriately altered to misrepresent findings.

In this scenario, the following points help clarify why falsification is the appropriate label:
- The researcher is actively changing the data pool after collection to shape the outcome, rather than reporting all data as observed.
- Excluding data to align results with a hypothesis can mislead readers and distort interpretation, which violates principles of honesty and transparency in research.
- Falsification is distinct from errors or honest mistakes in data collection; it involves deliberate alteration or selective reporting to achieve a specific conclusion.

Note on the provided answer options: the prompt’s answer_options field is empty, so we cannot analyze alternative choices. However, based on the described behavior, falsification is the correct characterization of the misconduct in this scenario.

If you had other options such as fabrication, selective reporting, or plagiarism, you would compare each by asking: Is data creation, data omission, or attribution inappropriate? Would the option involve inventing data, omitting data to mislead, or using someone else’s work without attribution? In this case, the key issue is the deliberate exclusion of data to bias results, which aligns with falsification.

CHM111L A Lab 0 Pre-Lab Quiz

A researcher collects a large number of data from several different experiments. She finds that not all data points support her hypothesis and so she excludes them from her final report. What type of research misconduct is this describing?

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