Question

The table shows results of an experiment that was replicated.


Which best describes the data?

They are precise and reproducible.
They are precise but not reproducible.
They are accurate and reproducible.
They are accurate but not reproducible.

Answer 1

I don’t see the table — I need the actual numbers (or an image) to pick one of those options. Paste the table or describe the replicate results (each replicate’s values and the accepted/true value if known), and I’ll pick the best description.

Meanwhile, here’s how to decide so you can check quickly:

- Accuracy = how close the mean of the measurements is to the true/accepted value (use percent error = |measured mean − true value| / true value ×100%).
- Precision = how tightly clustered the measurements are (use standard deviation or range).
- Reproducible (in this context) = the replicate experiment gives results similar to the original experiment (low difference between replicate means and similar spread).

Decision rules (common mappings):
- Accurate and reproducible: replicate means close to the true value and close to each other; low SD in each replicate.
- Precise and reproducible: replicate measurements cluster tightly and the replicate clusters are consistent with each other (they may or may not be accurate).
- Precise but not reproducible: original measurements are tightly clustered but the replicated experiment produced a different cluster (original precision did not reproduce).
- Accurate but not reproducible: means are near the true value but replicate results vary widely (high spread or inconsistent between replicates).

If you paste the data I’ll compute means/SDs and give the correct choice.