Clean data before trusting it — Data, 11–13 years
Blank answers, typing errors and mixed units can quietly change a conclusion. Data, 11–13 years.
Check the data
Data cleaning means finding entries that are missing, impossible, duplicated or written in different ways, then deciding how to handle them. It does not mean changing numbers to get a nicer result. It means making the data consistent while keeping a record of what was changed and why.
Why it matters
A computer treats 2 m, 200 cm and 2 as different text unless someone tells it they represent the same length. One extra zero or a repeated response can also distort a summary. Checking first prevents an accidental error in the recording from becoming a confident-looking claim.
Finding a bad entry
Five pupils record plant heights: 12 cm, 15 cm, 14 cm, 13 cm and 140 cm. The last value is possible only if the unit is wrong, so we check the original note. If it meant 14.0 cm, we correct the unit entry and record the correction. We do not quietly delete it or keep 140 just because it is written down.
Deleting the awkward value
When one value looks strange, it is tempting to remove it immediately because it makes the data look untidy. That temptation is reasonable: it may truly be a typing error. But it could also be a real result, so first check the source, the units and the measuring method, and explain any decision.
Where it helps
Hospitals check records before studying treatments, shops clean product codes before counting sales, and weather services check sensor readings. You meet the same problem when combining class survey answers: spelling, units and blank responses need a clear decision before anyone totals them.
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