Incomplete datasets can arise due to several reasons:
Data Collection Errors: Human errors during data entry or technical issues can result in missing information. Non-response: Individuals may refuse to participate in studies or fail to answer specific questions. Lost Records: Physical or digital records may get lost or destroyed. Sampling Bias: Certain populations might be underrepresented due to sampling methods, leading to incomplete data.
