1. Introduction to SPSS Opening the program Type in data Open an existing data set For now, click “Cancel”

2. Data vs. Variable View Opening a data file: Cars.sav* Cars.sav Variable View Data View Data from an SPSS sample data file called “cars”* Save a copy on your USB drive Use tabs at bottom to change views

3. Exploring SPSS, cont’d Exploring Menus and Toolbars Toolbar variables icon

4. Data View Right click on variable name to bring up a menu Value labels (vs. numeric data) can be toggled on and off from the View menu

5. Variable View Variable name Data type Number of digits or characters Number of decimal places Descriptive variable and value labels User-defined missing values Column width Measurement level

6. Values and Value Labels

7. Steps in Creating a Data File in SPSS 1. Make a determination as to how each variable in your research is to be measured and calculated (for example, is the “total attitude towards computing” to be the sum of the 20 items on the Attitudes toward Computing scale? Perhaps there were some items that you have determined through inspection aren’t useful, or perhaps you have some items that have to be “reverse coded” or for which there are many missing answers. a.Assign an Id number to each respondent. i.Protecting respondent privacy b.Name each variable. For example, the items on the Attitudes toward Computing Scale could be ATC1, ATC2,,,,,….ATC20. i.This name is a mnemonic for a longer variable name which you can assign. It should generally start with a letter and, to be compatible with older versions of SPSS, only 8 characters long, although current version can be 64 characters in most cases

8. Creating a Data File, 2 C. Specify the level of measurement (categorical or numerical, and if categorical, nominal or ordinal) D. Assign category values to the categories of each variable. Numerical values can be assigned the values they were given by the subject Categorical values (strongly agree, agree, neutral, disagree, strongly disagree; male/female) should be assigned numerical values such as 5,4, 3, 2, 1, where 5 equal “strongly agree” and 1 equals “strongly disagree;” male = 1 and female = 2, etc. E. Decide how you will deal with missing values. Do you want to include a response alternative of “don’t know” or “no answer” in the questionnaire or measure and then treat that choice of answer as “missing” in the data analysis?

9. Sample Questionnaire Below is how a fictitious respondent filled out some sample items from our study at St. Barnabas Senior Services Center. Respondent ID: 001 1. Are you _____XXX male ______female 2. Are you (please mark [XXX] one.) _____African American/Black _XXX Chinese/Chinese American _____Korean/Korean American _____Mexican/Mexican American _____White, non-Hispanic/Caucasian (please specify ethnicity, for example, Irish, Swedish, etc.) _____Other, please specify _________________________ 3. You are interested in knowing what your neighbors are like. XXX strongly agree agree neither agree nor disagree disagree strongly disagree 4. It’s hard to become friends with your neighbors. strongly agree agree neither agree nor disagree XXX disagree strongly disagree How many of your neighbors do you know well enough to ask them to do some of the following things? Write the number of neighbors in the blank. 5. Keep watch on your house or apartment? 2_____ 6. Ask for a ride? 3_____

10. Naming and defining Variables for SPSS: Decisions You Will Make Respondent ID: 001 1.Are you _____XXX male ______female Name: ID Categorical-Nominal 2. Are you (please mark [XXX] one.) _____African American/Black _XXX Chinese/Chinese American _____Korean/Korean American _____Mexican/Mexican American _____White, non-Hispanic/Caucasian _____Other Name: Ethnic Categorical-Nominal No Answer = 9 Multiple Answer = 8 African American/Black = 1 Chinese/Chinese American = 2 Korean/Korean American = 3 Mexican/Mexican American = 4 White, non-Hispanic/Caucasian = 5 Other = 6

11. Naming and defining Variables for SPSS, cont’d Four items measuring feeling of belonging to the neighborhood: 3. You are interested in knowing what your neighbors are like. XXX strongly agree agree neither agree nor disagree disagree strongly disagree Name=NBR1 Scale-Ordinal No Answer= 9 Multiple Answer = 8 Strongly Agree = 5 Agree = 4 Neither Agree nor Disagree = 3 Disagree = 2 Strongly Disagree = 1 4. It’s easy to become friends with your neighbors. XXX strongly agree agree neither agree nor disagree disagree strongly disagree Name=NBR2 Scale-Ordinal No Answer = 9 Multiple Answer = 8 Strongly Agree = 5 Agree = 4 Neither Agree nor Disagree = 3 Disagree = 2 Strongly Disagree = 1

12. Sample Questionnaire, 3 How many of your neighbors do you know well enough to ask them to do some of the following things? Write the number of neighbors in the blank. 5. Keep watch on your house or apartment? 2_____ Name: NBRHLP1 Scale=Scale No Answer = 99 6. Ask for a ride? 3_____ Name: NBRHLP2 Scale-Scale No Answer = 99

13. Using SPSS to define variables: The Steps You Will be Takinhg In SPSS, go to File/New Data, then click on the Variable View tab; we’re going to 1.Name each variable 2.Specify variable type, column width and decimals a.Variable type: string vs. numeric (or a variation of numeric) b.Width: how many digits you can enter for the variable, up to 8 c.Decimals: set at zero if data contain no decimals

14. Assign Labels, Values to Variables 3.Assign labels to each variable a.Variable labels may contain spaces or other symbols 4.Create values and value labels for each category of a variable a.Assign values for “don’t know” or “no answer” or “multiple answer” responses b.Assign values for scale alternatives such as “strongly agree” and “strongly disagree,” “male” vs. “female,” etc c.No need to assign values if the scale is strictly numeric (e.g. age, number of times something occurs, etc.) except missing values

15. Tell SPSS about Missing Values 5.Tell SPSS which values should be treated as missing and thus left out of computations. Enter the 9s, 99, 98, etcs. as ‘discrete” missing values 6.Format the columns for each variable 7.Identify the level of measurement of each

16. An example for the ID variable In Variable View, type the name of the first variable, ID, into the first row under “Name”. Note that default values are provided for the other variable attributes  The things you need to change are The number of decimals to 0 The label to the name “Respondent’s ID” Measure should be changed from Scale to Nominal

17. An example for the Ethnic variable  Now type in the name “ethnic” for your second variable, hit tab and the default values will be entered  You will need to change Decimals from 2 to 0 Provide a label for the variable (for example “Respondent Ethnicity”) Measure from scale to nominal

18. Adding value labels for “Ethnic” Provide Value Labels for the categories of the variable using the scheme developed earlier: African American/Black = 1 Chinese/Chinese American = 2 Korean/Korean American = 3 Mexican/Mexican American = 4 White, non-Hispanic/Caucasian = 5 Other = 6 Multiple Answer = 8 No Answer =9

19. Define missing data for “Ethnic” Recall that you decided to treat “no answer” and “multiple answer” as missing data, so enter their codes in the missing values dialog box Now would be a good time to start saving your file. Save it as practice1.sav

20. Enter the rest of your variables  Variables 3 and 4 have the same category labels and values and the same missing values, so you can use copy and paste to simplify your work  Just right click on the box on the value labels you want to copy from and select “copy”, then right click on the box of the value labels you want to copy to and select “paste”  Do the same with the missing values category

21. What the results of variable definitions should look like

22. Confirming Variable Definitions 8.When you have entered all of your variables, click the Data View tab to make sure all of your newly defined variables appear as column headings. Click on the variable icon on the toolbar to bring up the variables properties. Make corrections as needed.

23. Entering Your Data Let’s pretend this is the raw information from your coding sheet. In SPSS Data View, enter the data for these five respondents. You can turn value labels on or off depending on whether it helps you to enter data.

24. Checking Your Data Input Check your data. Turn on value labels. It should look like this: Compare the entries on the screen against the code sheet or raw data (surveys, measures) or Use the Analyze/Reports/Case Summaries feature to create a case-by-case listing of the data you input and compare against the code sheets or raw data Finally, save your data as an SPSS data file (Practice2.sav)