![]() ![]() You can use a general spreadsheet program like Microsoft Excel or a statistical analysis program like SPSS to create your data file. Now you are ready to enter your data in a spreadsheet program or, if it is already in a computer file, to format it for analysis. Instead, set them aside and keep notes about why you decided to exclude them because you will need to report this information. If you do decide to exclude any data, do not throw them away or delete them because you or another researcher might want to see them later. If information about the main independent or dependent variable is missing, or if several responses are missing or suspicious, you may have to exclude that participant’s data from the analyses. You will have to decide whether such problems are severe enough to make a participant’s data unusable. At this point, you might find that there are illegible or missing responses, or obvious misunderstandings (e.g., a response of “12” on a 1-to-10 rating scale). Next, you should check your raw data to make sure that they are complete and appear to have been accurately recorded (whether it was participants, yourself, or a computer program that did the recording). Professional researchers usually keep a copy of their raw data and consent forms for several years in case questions about the procedure, the data, or participant consent arise after the project is completed. It is also a good idea to make photocopies or backup files of your data and store them in yet another secure location-at least until the project is complete. Unless the data are highly sensitive, a locked room or password-protected computer is usually good enough. First, be sure they do not include any information that might identify individual participants and be sure that you have a secure location where you can store the data and a separate secure location where you can store any consent forms. Whether your raw data are on paper or in a computer file (or both), there are a few things you should do before you begin analyzing them. In this section, we consider some practical advice to make this process as organized and efficient as possible. There might even be missing, incorrect, or just “suspicious” responses that must be dealt with. Furthermore, the “raw” (unanalyzed) data might take several different forms-completed paper-and-pencil questionnaires, computer files filled with numbers or text, videos, or written notes-and these may have to be organized, coded, or combined in some way. It is likely that for each of several participants, there are data for several different variables: demographics such as sex and age, one or more independent variables, one or more dependent variables, and perhaps a manipulation check. Describe the steps involved in preparing and analyzing a typical set of raw data.Įven when you understand the statistics involved, analyzing data can be a complicated process. ![]()
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