To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including: Questions and Inquiriesįor inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. Please note that other Pearson websites and online products and services have their own separate privacy policies. This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site. For example, you might have obtained and recorded the weight in pounds for 20 people, as shown in Figure 1.1 When you run a statistical analysis, your purpose is generally to summarize a group of numeric values that belong to the same variable. Values vary from person to person and from object to object-hence the term variable. The number 20 is a value of the variable Age, the name Smith is a value of the variable Surname, 130 is a value of the variable Weight in Pounds, and Ford is a value of the variable Brand of Car. Database jargon often refers to variables as fields, and some Excel tools use that terminology, but in statistics you generally use the term variable. Surname is a variable, and so are Weight in Pounds and Brand of Car.
It describes all humans, all living organisms, all objects-anything that exists for some period of time. To illustrate one useful arrangement, you won’t go wrong if you put different variables in different columns and different records in different rows.Ī variable is an attribute or property that describes a person or a thing. In fact, some of Excel’s features don’t work at all if your data doesn’t conform to what Excel expects. 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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