1Chapter 2Basic OperationsChapter 1 presented a very conceptual overview of SPSS. The present chapter will walkyou through the routine procedures that you will use nearly every time you work with SPSS.Specifically you will learn how to navigate the SPSS environment, enter save and retrieve datasets; create, modify, and save text based records of procedures you preform (syntax); andgenerate, navigate, save and print the results of your data analyses (output).Three WindowsFor the most part SPSS can be split up into three major parts: The Data Editor (where weenter data and create new variables), The Syntax Editor (where we store & create syntax for ouranalyses and procedures), and The Output Navigator (where we view the results our statisticaltests have generated). Each of these parts of SPSS has its own program window in SPSS. Whenall three are open there will be three separate buttons for SPSS on the windows task bar (SeeFigure 2.1a). You can navigate between the three windows by clicking on the appropriatebuttons on the task bar. When working in the windows, if you close either the Output Navigatoror the Syntax Window the remaining windows will not be affected. Closing the Data editorcloses SPSS, and the Output Navigator and Syntax Editor will close as well.2Data EditorThe first step in any data analysis process is to set up the data file in the Data Editor(note: you can create variables and enter data in the syntax editor, but it is beyond the scope ofthis text). The SPSS Data Editor is split into two parts (or views): The Variable View and theData View. The Data View allows you to view and input data. The columns represent Variablesand the rows represent observations/participants/subjects (often referred to as cases). TheVariable View allows you to edit variables and add new variables to the data stet. Note that therows represent each variable and correspond to the columns in the data view. Also, the columnsin this view represent different aspects of each variable. Figure 2.1 presents the Variable Viewand the Data View for a blank file in the data editor. Part A represents the variable view and partB represent the data view.To toggle back and forthbetween the “Data View”and the “Variable View”Click on the labeled filetabs located at the bottomleft hand corner of thedata editor spread sheet:We have marked themwith the letter “C.”3Creating New VariablesCartoon 2.1 is the back drop for the data set that you will work with for this chapter.Helga’s statement about Hagar implies that he would not know what the well water tastes like,because he only drinks beer. Beer holds a special place in the hearts of most statisticians, assome of the basic statistical procedures and assumptions used today were developed by WilliamGossett, an employee of the Guinness brewery in Ireland. In the late 1800, Gossett developed thestudent t-distribution so that he could estimate the quality of a barley shipment (a population ofscores) based on a random sampling from the shipment. Thus, without beer there would be nostatistics. Though you may argue that without statistics there would be little need for beer. Itseems likely that both statements are true.With respect to the data set, assume that a researcher is interested in the drinking habitsof different cartoon characters. Specifically, she is interested in the types of beer consumed bycartoon characters and the amount. Type of beer would be considered a discrete (and nominal)variable that represents groups. Amount in this case is operationalized the number of beers (12oz cans) consumed per week and will be treated as continuous (and ratio) variable. If the4distinction between discrete and continuous scores is unclear to you, go back and review thediscussion in Chapter 1. Table 2.1 displays the result of the study. The first column of numbersrepresents the participant numbers that are used help keep track of each individual cartooncharacter’s data. The second column presents the number of beers consumed per week by eachcharacter. The third column presents the brand of beer preferred by each character. To create new variables on a blank datafile, select the variable view. Note that novariables are listed. 1) Give the variable aVariable Name by typing the desired name in thefirst open row of the first column, labeled Name.Table 2.2 presents a summary of the variablenaming do’s and don’ts. SPSS 14 allows you tohave 64 characters in the name, however it is agood idea to keep names as short as possible (lessthan 10 characters is a good rule of thumb). TheName can not start with a number, though it canhave numbers in it. Nor can it have any spaces orsymbols (i.e., % ^ & * + ~ ( ) { }[ ] / > <) in it,with the exception of the following: @, #, $, and_. You can use periods (or decimal points), but not at the end of the the variable name. Otherforms of punctuation can not be used (! , ; : ? ‘ ’ “ ”). Figure 2.2 presents the variable view for afile where we have defined two variables. Based on Cartoon 2.1, our variables represent the5number of beers cartoon characters drink a week and the brands of beer that cartoon charactersdrink. In our example we have named the first variable beerweek. Similarly, we have named thesecond variable beerbrnd.2) Give the variable a “Variable Label”, by clicking the appropriate cell in the Labelcolumn. Variable Labels are more flexible than Variable names. You can have more than 200characters and you can use spaces and symbols. The variable label allows you to give a moredescriptive name to the variable that will make sense to you when you come back and look atyour data after a long period of time has elapsed. Be as precise as possible. Also, when you givea variable a “Variable Label” the variable label will appear on the output of your analyses (wecover output later in this appendix). However, note that labels more than 40 or so characters will6be truncated on the output (it will only present the 1st 40 characters), so put the most unique anddescriptive information first. Otherwise your outputs may become vary confusing. In ourexample we have given the beerweek variable the variable label “Weekly Beer ConsumptionData Set,” and we have given the beerbrnd variable the variable label “Brands of Beer DataSet.”3) If the variable represents groups (a discrete/nominal variable; e.g. sex/gender,ethnicity, group membership) then you will need to define the Value Labels. You do not need todo