'It is exceedingly difficult to explain many statistical concepts in terms that are both technically accurate and easily understood by those with only a cursory knowledge of the topic.'This wise note appears at the opening of a valuable book on reporting statistics [4]. In this series so far, we have tackled this difficult task, and accommodated the need to 'avoid the fine points and distinctions that would detract from an explanation otherwise adequate for most readers'. In other words, we are writing for a readership of science authors and not for professional statisticians. Even statisticians differ between one another in their preferences and procedures, and for consistency we shall continue to use the book cited above (apart from small deviations) as the basis for a uniform set of suggestions. Ultimately, this will become a substantial list, but we wiE cross reference this list to the concepts and principles we address in further articles. In this long list of suggestions, we shall give reasons for making these suggestions. A good analogy is a cookery recipe. It helps if you're told why things are done in the way suggested, and the principles (as long as they are sound!) are explained clearly. We can extend this analogy: food writers themselves have differences; the best writers recognize that ingredients differ, and even the infrequent cook knows that precise weights and measures need not guarantee a successful dish.
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