![]() Excel is generally very flexible about how and where you put the data you’re interested in, but when it comes to preparing a formal analysis, you want to follow some guidelines. When you lay out your data without considering how you will use the data later, it becomes much more difficult to do any sort of analysis. When you put the statistics into tables and charts, you begin to understand what the numbers have to say. With your data laid out properly, you can easily and efficiently combine records into groups, pull groups of records apart to examine them more closely, and create charts that give you insight into what the raw numbers are really doing. And how you choose to represent data in Excel has implications for how you run the numbers. But variables and values, along with scales of measurement (covered in the next section), are at the heart of how you represent data in Excel. It must seem odd to start a book about statistical analysis using Excel with a discussion of ordinary, everyday notions such as variables and values.
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