Survey Data Laundering is a process how to split up the survey data into some highly reliable blocks. Then we can reconstruct the data back from those blocks into primary data table format, where some non-matching/doubtful answers are removed. The analyst's conclusions will be more accurate after the laundering has been performed. A typical example is a respondent satisfaction with services offered, see example.

If a company executive needs to zoom in on the Internet surfing in his company, provided that it is a principal concern of his, he should do this, by asking himself the following key question: "What distinguishes the 'spiders' from their non-surfing colleagues, and which websites catches their attention (and time!)". To find the answer,...

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