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Instead, they scan the text and pick out headlines, highlighted words, bulleted lists, and links.
In many ways, this problem is quite similar to that experienced with direct quotes.
Too often, quotes are expected to do all the work and are treated as part of the argument, rather than a piece of evidence requiring interpretation (see our handout on how to quote.) But if you leave the interpretation up to the reader, who knows what sort of off-the-wall interpretations may result?
The only way to avoid this danger is to supply the interpretation yourself.
But before we start writing statistics, let’s actually read a few. This is one of the reasons why statistics can be such persuasive pieces of evidence.
The average reader does not know how to properly evaluate and interpret the statistics he or she reads.
The main reason behind the poor use of statistics is a lack of understanding about what statistics can and cannot do.
Thus, the guideline is: For now, sites that sell computer equipment should spell out and explain TB when they use it.
In a few years, people will be accustomed to the unit and won't need such explanations.
When writing for the Web: As an example of the latter, if I say something like "in recent years, we have tested thousands of users and seen their use of breadcrumbs increase," it's better to write "thousands" as a word than to write "1,000s" or something like that.
"Thousands" is not really data in this context, it's intended to give an idea of the scope of the research.