1.  SPSS WORKSHOP  Please Sign onto Your Computer Station User Name: Password: Domain: ASU.EDU (Kerberos Realm) If you have trouble signing in: User Name: westguest Password: asuwest Domain: C104_0X (this computer) If still having trouble, then please raise your hand

2. Brief Introduction to Statistics with SPSS Joe Ryan, Research Consulting Center Rico Rivera Cindy Owens Josh Fox Statistics Laboratory http://www.west.asu.edu/rcc/

3. Workshop Objectives (p 2) • Understand Basic Organization of SPSS • How to input, save & retrieve raw data • How raw data file is edited in variable view • Creating new variables by transforming • Perform basic data analyses

4. Open up your internet Explorer http://www.west.asu.edu/RCC • Click on the Stat Lab button (located on left side) • Click on Workshops • Click on Data used for Workshops • Click on Fin_Health_edited_data.sav • Please save it in your Desktop. • Close the internet brower.

5. SPSS Accessibility (p. 3) • Network access • Technopolis (basement of library) • Desktop (hard drive) installed • Computer Classrooms • Stat Lab

6. Accessing the Statistic Laboratory • Location: CLCC 107 • Phone: (602) 543-6117 • Website: http://www.west.asu.edu/RCC • Operating hours: See website • When using the lab, please sign in at the front counter

7. Support for Statistics (p. 4) • Function of Stat Lab (also pp. 18-20) • The Stat Lab staff assists students with aspects of statistical software. • The Stat Lab is not set up to provide one-on-one tutorial service for students on a regular basis. • However, we have and frequently do answer general statistic questions. • Statistics Tutoring • Learning Enhancement Center • TRiO (SSS) program

8. Overview of the Research Process Page 5 DISCUSSION SECTION Interpretation Were the hypotheses supported? Why or why not? Any limitations? What are the Implications? Suggestions for further research? RESULTS SECTION Data Analysis Descriptive Statistics Inferential Statistics METHODS SECTION Measures or Instruments Validity - What did we measure? Reliability – How precise was the measure METHODS SECTION Participant Characteristics Who did you sample? Procedures How did we do the observations? AT THE END OF LITERATURE REVIEW OR INTRODUCTION Based on theory & literature review, what is (are) the question(s) you want to address? What are respondents’ attitude toward their financial and health conditions? Are attitudes toward financial and health conditions related? Do males and females have different attitudes? Do participants in different age groups have different attitudes? Research Consulting Center Statistics Lab CLCC 107 www.west.asu.edu/rcc (602) 543-6117

9. Procedures for Data Analysis (p. 6) Data  StatPak  Output  Interpretation • Collect & organize data • Input & edit the data • Transform Variables • Analyze data or create graphs • State results and interpret

10. Please fill out the survey (Remove the last page of your handout) • Response • Strongly Disagree • Disagree • Agree • Strongly Agree • Sex • Male • Female • Age • Under 25 • 25 – 40 • Over 40 • Response • Strongly Disagree = 1 • Disagree = 2 • Agree = 3 • Strongly Agree = 4 • Sex • Male = 1 • Female = 2 • Age • Under 25 = 1 • 25 – 40 = 2 • Over 40 = 3 • Having ID column will help you keep track of cases • What do the first five questions measure? • What do questions 6 through 10 measure?

11. Let’s Launch SPSS • Menu Bar • Data & Transform are used to manipulate the data in data editor (i.e., spread sheet) • Analyze and Graphs are used to create output • Tabs (bottom left hand corner of data editor, p. 7) • Data View • Columns: Variables (e.g., questions on survey) • Rows: Cases (e.g., survey) • Variable View • How we edit the variables • Give variables their names, labels, etc • Enter you survey into Data View

12. Editing the raw data • Variable View • Tab (located lower left hand corner) • Pages 9 – 10 of your handout

13. Transforming Variable (p 11) • Recode • Data may be need to be recoded for a variety of reasons • Examples • common for reversing the scales • Converting a continuous variable into discrete ordinal variable • Transform > Recode > Into Different Variables • Computing a New Variable • Can create new variables that may be a function of pre-existing variables • Transform > Compute

14. Statistical Functions(supplemental information) • Table on pages 12-13 • Statistic • Function/description • SPSS procedures

15. What are the Levels of Measurement? (supplemental information: p. 17) • Ratio (e.g., lengths, weights, volumes, capacities, rates): • Different categories • Rankable categories • Constant equal-sized Intervals • Absolute Zero (physical significance) (e.g., temperature in Kelvin, time) • Interval (temperature on Celsius and Fahrenheit, age): • Different categories • Rankable categories • Constant equal-sized Intervals (can be expressed numerically) • Ordinal (e.g.., dominance hierarchy): • Different Categories • Categories are rankable • Nominal (a.k.a. attributes) • Different Categories (e.g.., sex, species, phylum, location)

16. Thanks for having us  Do keep the “Financial and Health Attitude Survey” you filled out. Please close SPSS & log off your computer. Please turn in the “SPSS Workshop Evaluation” as you leave the room. Have a good day. 