Some daily values are missing from an observation table. What should be done before drawing a conclusion?

Correct answer: Examine the cause and effect of missing data

The direct answer is B: examine the cause and effect of the missing data. A conclusion should be based on trustworthy evidence. If values are absent, we must first ask why they are missing: perhaps an observation was not made, an instrument failed, or a record was lost. We should also consider whether the missing values could change the pattern or trend. Option A is wrong because inserting desired numbers is fabrication and introduces bias. Option B is correct because checking the reason and possible effect protects the reliability of the conclusion. Option C is too extreme: the whole table need not be discarded; useful recorded data may still remain. Option D is wrong because selecting the largest value ignores the rest of the evidence and cannot replace missing observations. A careful investigator marks missing values clearly, investigates them, and avoids pretending that unknown data are known. Exam cue: never fill a gap with a convenient value unless a justified method is explicitly provided.