Abstract
Good practice' has a place throughout applied statistical work, and involves the habitual taking of reasonable precautions against mistakes and misunderstandings. The procedures of good statistical practice are founded on experience and commonsense. The time and effort that they require are well spent. Although comprehensive Codes of good statistical practice might be too cumbersome to be useful, specific procedures can readily be described and statisticians should be trained in them. Checking is a key element of statistical good practice. Also, the practitioner should aim to be proficient in writing clear prose, in drawing clear diagrams, and in producing numerical tables that tell their story clearly.
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