Inconsistent Data Recording in Experimental Results

During the experimental session, some recorded data points appear inconsistent or missing when exporting results. This may lead to inaccurate analysis and conclusions. A review of the data logging process is needed to ensure all experimental results are properly captured and stored.

Steps to Reproduce:

1. Conduct an experiment and record data using the provided system.
2. Export the results into a spreadsheet or database.
3. Compare the recorded values with expected measurements.
4. Identify missing or inconsistent data points.

Expected Result:

• All experimental data should be recorded accurately.
• The exported dataset should match the observations without missing values.
• Any errors in data logging should be flagged.

Actual Result:

• Some data points are missing or inconsistent in the exported file.
• There is no clear indication of data loss or errors.

Possible Solution:

• Implement automatic validation checks during data entry.
• Add a logging mechanism to track missing or inconsistent values.
• Ensure proper synchronization between data collection and storage.