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If you plan to use a statistical analysis package, you will need to be thoroughly familiar with its rules and procedures for setting up a data file. Each software package also has its own rules for data entry, the process of entering the codes for the attributes of variables into the data file. Most packages have extensive tutorials that teach how to perform these operations. In addition, you probably can get help from persons with experience in using software programs available at your university. Regardless of the help you might get, it is a good idea to enter data for a small number of cases and do some test runs for analyses you plan to do later. This way you can discover and correct errors before beginning you final analyses. If your university does not have a software package already installed, there are a number of packages available free from Web sites. Here are some of the ones we found after searching google.com for free software packages: BTS Guide to Good Statistical Practice in the Transportation Field, from the U.S. Bureau of Transportation Statistics, a guide on how to present data analyses and discussion of data quality and errors Census and Survey Processing System, provided by the official statistical body of the U.S. government, the Census Bureau, this package includes free software for entering, tabulating, and mapping census and survey data Data Analysis with Epi Info, a free source for Epi Info, a statistical analysis package; provides for data entry and a wide range of statistical analyses Free Software, an extensive guide with links to a variety of statistical analysis packages and related resources; also provides links to guides for making statistical calculations Web Pages that Perform Statistical Calculations provides over 600 links, including nearly 400 pages that perform calculations, and growing; a source of information on almost anything you might need in conducting analyses and calculations Even if you decide to use computer analysis, you will probably need to do hand tallying of data at some point in your research. If you do an exploratory study, for instance, you might want to hand tally the data for the few cases involved. Also, occasions arise when you may wish to look at some variable without having to enter the data into a computer. An important step in data preparation involves coding. Coding is essential for computer analysis because computers can only "read" numbers. If you tally your data by hand, coding will help reduce errors. Coding Coding is the process of assigning numbers to represent the attributes making up variables. Coding can be done before or after data are collected. In Chapter 10, we gave examples of coding responses to closed items at the time the items are written. Examples of precoding are provided in Tables 10.1 and 10.2. The codes appear on the questionnaire and are used by the interviewer in recording responses to the items. Coding closed items Coding closed items is relatively easy and straightforward. However, the level of measurement has to be taken into account. For responses measured at the nominal level (male/female, single/married/etc.), any set of numbers can be used. For such variables, numbers simply identify categories and have no value in relation to one another. You could use "1" for male and "2" for females or the reverse or any other set of numbers. For variables measured at the ordinal level, codes assigned to attributes have real value. With ordinal measurement, the attributes can be ordered along some dimension. Responses of "strongly agree," "agree," "disagree," and "strongly disagree," for example, represent points along a dimension from agreeing to disagreeing about some issue. Typically codes of 0, 1, 2, and 3 or 1, 2, 3, and 4 are used for responses to items like these. The numbers used as codes preserve the idea of ordered variation among the responses. Interval and ratio measurement produce numbers that do not require coding. |