Introduction to SPSS on the Macintosh. Scott Patterson,Ph.D. Broadcast and Electronic Communication Arts San Francisco State University.

Transcription

1 Introduction to SPSS on the Macintosh. Scott Patterson,Ph.D. Broadcast and Electronic Communication Arts San Francisco State University Spring 2000 This is a brief guide to using SPSS in the Macintosh Operating Environment. The rules are similar in the Windows Operating Environment, you should be able to make the shift from this guide to a Windows version of SPSS. Just be aware some terms are different. If you have difficulty, ask your instructor. This guide presumes user knowledge of the Macintosh Operating System, Basic file management using external storage media (zip disk or floppy), and knowledge of basic word processing (MS Word for example) and basic spread-sheet operations (MS Excell). Basic Orientation. SPSS for the Mac consists of four different operating components: The Data Window Where the raw observations (data) are recorded. This is the window that looks like a spread-sheet (with rows and columns). If you create or modify a variable, it will appear in the data window.

2 The Syntax Window Where you can create syntax (a list of commands) for SPSS to execute. You can execute commands from the syntax window or from the drop down menus. Many of the command screens give you the option to paste syntax into the syntax window.

3 The Chart Carousel Where charts and other graphic output is directed. Part of understanding SPSS is to learn which window is used for what purpose. The majority of work in your first lab will be in learning how to create a data file that contains raw data and definitions of the variables. The Data File The first step in working with SPSS to create the definitions in the data file. Every variable gets its own unique column in the data set and every row is a specific case (a completed survey for example).

4 In the above window, the columns titled acchome (do you access the Internet from home?) and accwork (do you access the Internet from work?) represent questions asked on a survey called (BEV Combined.SPSS.DEF). Each row (#1, 2, 3, 4, etc..) down the left-hand side of the window (in the gray bar) represents an individual respondent. For example, respondent #1 recorded a score of 1 for acchome and 1 for accwork (a yes ) while respondent #7 indicated a 2 for acchome and a 1 for accwork (h/she accesses the Internet from work but not from home). Respondent #6 recorded a score of 2 for the variable accoth. Before you can enter any data (observations) into SPSS you must first define the variables with which you will be working. To illustrate how to create an SPSS data set, we will create a dataset for keeping track of the grades in BECA 390. The BECA390 Gradebook. BECA 390 is a class with 75 students. For each student we will record the following information:

5 Variable Variable Type ID Number String ( ) First Name String Last Name String Exam 1 Score Numeric (Ratio level) Exam 2 Score Numeric Exam 3 Score Numeric Still prior to doing any programming, we need to gather more information. SPSS asks that each variable be given a unique variable name. SPSS has some very specific rules for creating variable names: names can have no spaces or punctuation. names must be all lowercase letters and numbers names must be NO LONGER than 8 characters Variable Variable Type SPSS Variable Name ID Number String ( ) id First Name String first Last Name String last Exam 1 Score Numeric (Interval level) exam1 Exam 2 Score Numeric exam2 Exam 3 Score Numeric exam3 Now we have the minimum amount of information we need to create our data file definitions. Step 1 Start SPSS by double-clicking on the SPSS icon:

6 Step 2 SPSS should default open to a blank data window. From here, define the first variable (id) by using the data drop-down menu: The Define Variable Command brings up the define variable dialog box. In this box, first type the name of the variable and then click the type button:

7 The type button brings up the type dialog box where you indicate id is a string variable: Notice you can also tell SPSS how many characters you will allow for the variable. In this case we chose 15 since our ID number takes a minimum of 12 characters. Click Continue to go back to the define variable dialog box. You can do many other things in the variable dialog box that aren t important to the BECA 390 grade book. For example, if we had a variable called class rank that we recorded as a numeric variable so we could use it in statistical analysis (we can t use string variables in statistical analysis). We would use the Labels button to bring up a dialog where we could assign words to the numbers recorded in the database:

8 You should always choose compress spss data. You should create the other five variables for the BECA 390 Gradebook Data Set now. The completed data window should look something like: Entering Observations into the Data Window

9 A second way of entering observations is to cut and paste different rows or columns in from another spread-sheet application like Microsoft Excell. This cut and paste method is especially helpful for gradebooks at SFSU as the university computer center will provide you with an electronic version of your class list in the Microsoft Excell Format. For this assignment, I provided you with a complete list of the BECA 390 student id numbers, first and last names in Microsoft Excell. You can just cut and paste and entire Excell spread-sheet into the SPSS Data Window. To do this: 1. Open the Excell Document and the SPSS Data Window 2. Select all of the columns and rows you want to cut and paste 3. Select cut or copy from the edit menu 4. Switch (using the multi-finder) to the SPSS Data Window 5. Click on the first cell (row 1, column 1). 6. Select paste from the edit menu. 7. SAVE SAVE SAVE SAVE. A third way of entering observations is VERY COOL. This technique is the one you will probably use the most. This technique involves importing observations into the SPSS Data Window. Let s get away from the gradebook example for a minute and imagine we had around 400 surveys of data we needed to enter into the Data Window. To do each of these by hand in either SPSS or Excell would be very time consuming because of all the extra key-strokes you need to use to navigate among the cells (tab, return, and enter). It would be easier to enter all the observations (numbers representing responses) into the computer using a word processor and then to save those observations as a text file:

10 instructed to save each individual survey in a text file with a tab between each answer and a hard-return after each last answer (the four digit id-number 5592). Importing text from a text file is one of the easiest ways to import data to spss. To import data from a text file, you can do it in one of two ways. You can use the read ascii data option from the file menu and the follow the menus to define your data set. The advantage of the read ascii data command is that you do not have to define your datafile before you import the data. However, to use the read ascii data, you really need to know how your dataset is constructed. I prefer to read my text (ascii) files first into Microsoft Excell (which has an excellent text import function) and then do a cut and paste as explained above. Creating New Variables in the Data Window Once we have our raw observations entered into the data window, we may need to create new variables based on some combination of observed variables. For example, in our gradebook, we might need to create a new variable called totpts that represents the total points earned on the three examinations. We also might want to calculate a new variable that represents the percentage of available points earned by a student. We will call this variable totper. Variable Variable Type SPSS Variable Name ID Number String ( ) id First Name String first Last Name Numeric (Interval level) exam1 Exam 2 Score Numeric exam2 Exam 3 Score Numeric exam3 Total Points Numeric totpts Percentage of all points Numeric totper To calculate new variables from existing variables, use the compute command from the

11 This command will bring up the compute dialog box where you can specify how variables are to be used to create a new variable. To create the new variable totpts the compute dialog box should look like this:

12 Notice you can click on the button Type and Label to define the variable just like you did above. You can also use mathematical operations and special functions to help you define variables. For example, we know there were 300 points possible in the class so I can figure out what percentage of 300 points every student earned. To do this calculation, we would use the compute function and the dialog box would look like this: The data window now shows the new variables we have computed. Notice the totper variable now has two decimal places (done via the type and label button) because it is a percentage. Recoding Variables in the Data Window Recall in class we spoke about reversing the valence on scaled items to avoid response set. We have to remember to reverse the scaling of these items before data analysis. To rescale items or to reduce the number of categories (for example going from a measure of age at the ratio level to a measure of age by categories (young and old)) we use the recode command. To reverse the

13 To recode a reverse valence Likert item with five points we would need to take a score of 5 and give it a score of 1, a score of 4 a score of 2, a score of 2 a score of 4, and 1 to 5, three stays the same as the middle point. The recode dialog box for this operation would look like: Where you identify the variables to be recoded. It is possible to recode multiple variables at one time. When you have selected the variables to be recoded (likert1), you then click Old and New Values to define the recode:

14 You need to define each recode individually and add it to the list of recodes. When you are done, you click continue and then OK to do the recodes. Remember to Save. These are the basic steps you need to know for moving around the SPSS data window. Understanding the data set is the most difficult part of learning SPSS. We will spend significant time learning how to construct and work with data files.