An inadequate quality assurance program can compromise the _________ and _______________ of the experimental results.

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Multiple Choice

An inadequate quality assurance program can compromise the _________ and _______________ of the experimental results.

Explanation:
Quality assurance is about ensuring that the data you obtain are trustworthy and can be trusted by others. When QA is inadequate, errors, bias, or procedural drift can creep in, which means the measurements may not reflect what they’re supposed to measure (compromised validity) and the results may not be able to be duplicated under the same conditions (compromised reproducibility). These two aspects—validity and reproducibility—are what QA most directly protects and verifies in experimental results. The other options don’t fit as well because they refer to things QA doesn’t primarily determine. The “number” and “significance” relate more to study design and statistical outcomes than to the integrity of how data are collected and reported. The “frequency” and “extent” of measurements describe scope rather than the trustworthiness of the results. And “quality” and “quantity” describe general attributes of data, not the specific pair of concerns that QA is meant to safeguard.

Quality assurance is about ensuring that the data you obtain are trustworthy and can be trusted by others. When QA is inadequate, errors, bias, or procedural drift can creep in, which means the measurements may not reflect what they’re supposed to measure (compromised validity) and the results may not be able to be duplicated under the same conditions (compromised reproducibility). These two aspects—validity and reproducibility—are what QA most directly protects and verifies in experimental results.

The other options don’t fit as well because they refer to things QA doesn’t primarily determine. The “number” and “significance” relate more to study design and statistical outcomes than to the integrity of how data are collected and reported. The “frequency” and “extent” of measurements describe scope rather than the trustworthiness of the results. And “quality” and “quantity” describe general attributes of data, not the specific pair of concerns that QA is meant to safeguard.

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