1. Understanding SPSS Brandon Aragon, Research Technician Eric Cazares, Graduate Assistant Claudia Alvarado, Graduate Assistant 2015-16 Workshop Series October 20, 2014

2. Office of Institutional Research (IR) Accountability Internal External Assessment Continual Improvement Support Surveys and Measures Planning Enrollment Management/Resource Allocation Decision-making and Policy Formation Research Qualitative and Quantitative Research Dissemination Visit us at: http://ir.csusb.edu

3. IR Staff AVP for Institutional Effectiveness and Director of IR Muriel Lopez-Wagner Assistant Director Tanner Carollo Institutional Effectiveness Associate Joanna Oxendine Research Technicians Allan Taing and Brandon Aragon Administrative Support Coordinator Monica Villarruel Graduate Research Assistants Eric Cazares, Claudia Alvarado, Lesley Quinonez, Keiry Borruel

4. What is SPSS? Statistical analysis software Descriptive statistics and frequencies T-Tests, ANOVA, correlations, etc. Tabulated reports, graphs, and charts. Can also be used for data management

5. SPSS or Excel? Some benefits of using SPSS over Excel include: Quick and easy access to descriptives Variety of charts and graphs Flexible pivot tables Easy to create subsets Easy value labeling User friendly with output that is easy to understand

6. Opening Excel Files Open SPSS Opening Window Recent Files Open a dataset File -> Open -> Data File Type: SPSS Statistics (*.sav) Excel (*.xls, *.xlsx, *.xlsm) Read Variable names from the first row of data Save File

7. Data View Each row is a different case Each column is a different variable Can drag and move variables (unlike Excel) Variables can be used to group participants (ex. “program”) Change to Variable View Click Variable View tab Double-click variable

8. Variable View: Describing your Data Edit Variables Each row is a variable Name Edit variable names No special characters (spaces, $, /, etc.) First character has to be a letter Type (String = alphanumeric, Numeric = numbers only) Width Change GPA to 2 decimal places No decimals for ID Label: Full Name from Excel

9. Variable View: Describing your Data (cont’d) Value Labels Gives a label to simple values Gender: 1 = Male, 2 = Female Missing Values Force SPSS to exclude a value EX: GPA = 99, Class Level missing value Align Similar to Excel Measure Nominal – Gender Ordinal – Level Scale – GPA Can copy/paste Labels, Values, and Missing Change to Data View Click Data View tab Double-click variable number

10. Search (case/variable) Data View Click GPA -> Ctrl+F Variable View Click Name/Label -> Ctrl+F

11. Frequencies and Descriptives Frequencies Analyze -> Descriptive Statistics -> Frequencies Class level, GPA, Gender, Program Statistics and Charts buttons Interpret (Frequency, Percent, Missing ClassLevel) Descriptives Analyze -> Descriptive Statistics -> Descriptives GPA, Gender Interpret (N, Minimum, Maximum, Mean, Gender) Remove Missing value from GPA Right click variable -> Descriptives Interpret (Different way to get information, different mean because of Missing)

12. Program Exercise Rename the “Program” variable so that it represents a program that is relevant to your area of expertise. Enter a number for each case (values) 1 = Participant, 2 = non-Participant Add variable values Check the characteristics of the variable to make sure they are appropriate.

13. Select/Split Cases Data -> Split Files Move program into the box, check ‘Compare groups’ Obtain the Descriptives of GPA Data -> Select Cases If condition is satisfied Gender = 1 AND ClassLevel = ‘Freshman‘ Filter out unselected cases Copy Selected cases to a new dataset Delete unselected cases Descriptives of GPA

14. Crosstabs Analyze -> Descriptive Statistics -> Crosstabs Select and drag row/column variables Statistics Cells - Percentages Create separate tables to analyze: Class Level by Program Participants Gender by Program Participants

15. Custom Tables Analyze -> Tables -> Custom Tables Select and drag row variable(s) Select and drag column variables(s) Summary Statistics Adjust counts and percentages Add Column N% Add Table N% Categories and Tables Totals Category order Create separate tables to analyze: Class Level by Program Participants Gender by Program Participants

16. Computing New Variables/Recoding Transform -> Compute Variable Target Variable – New Variable Compute Honors if GPA >= 3.5 Recode Missing Value Tranform -> Recode into Same Var. Old & New Values Old Value = System-missing New Value = 0 Click Add

17. Custom Tables (Part II) Create a custom table to analyze Class Level by Honors and Gender Versatility of customs tables allows for multiple layers to be added A more complex example - Analyze Program and Class Level by Honors and Gender

18. Thank You! Questions/comments? Contact Us AD-170 909-537-5052 institutional_research@csusb.edu