Note: This procedure was introduced in SPSS version 17 ( source: SPSS v23 Command Syntax Reference). You can generate this detailed codebook using the Codebooks dialog window, or using syntax. Also unlike the simple method, the summary information for each variable will be printed in its own table. Unlike the simple method, you can choose which variables are included in the codebook, and you can choose which variable properties are included in the summary. This codebook method includes all of the same information as the simple method, but also includes options for printing summary statistics as well. The codebook will print to the Output Viewer window.Click File > Display Data File Information > Working File.You can generate this simple codebook using the point-and-click menus, or using syntax. It also prints a table with the assigned value labels for categorical variables. It gives the names, labels, measurement levels, widths, formats, and any assigned missing values labels for every variable in the dataset. This codebook method prints most of the information found in the Variable View window. If you are not familiar with variable properties (such as labels or measurement levels) or concepts like value labeling of category codes in SPSS, you should read the Defining Variables tutorial before continuing. Many codebooks are created manually however, in SPSS, it's possible to generate a codebook from an existing SPSS data file. A good codebook allows you to communicate your research data to others clearly and succinctly, and ensures that the data is understood and interpreted properly. For categorical variables: If coded numerically, the numeric codes and what they representĬodebooks can also contain documentation about when and how the data was created.For scale variables: The variable's units of measurement.numeric, string how many characters wide it is how many decimal places it has) How the variable was actually recorded in the raw data (i.e.What the variable represents (i.e., its label).A codebook is a document containing information about each of the variables in your dataset, such as:
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