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Introductory Workshop SPSS

Introductory Workshop SPSS. CSU Bakersfield December 9, 2005. Acknowledgements . Kaye Bragg, Director, Faculty Teaching and Learning Center Peggy Leapley, Nursing. Facilitators. Ed Nelson – CSU Fresno ednelson@csufresno.edu Jim Ross – CSU Bakersfield jross@csub.edu

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Introductory Workshop SPSS

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  1. Introductory WorkshopSPSS CSU Bakersfield December 9, 2005

  2. Acknowledgements • Kaye Bragg, Director, Faculty Teaching and Learning Center • Peggy Leapley, Nursing

  3. Facilitators • Ed Nelson – CSU Fresno ednelson@csufresno.edu • Jim Ross – CSU Bakersfield jross@csub.edu • Campus representatives for the Social Sciences Research and Instructional Council (SSRIC)

  4. Social Science Research and Instructional Council (SSRIC) • Discipline council for the social sciences made up of representatives from each campus in the CSU. List of campus representatives can be found at http://www.ssric.org/reps • Promotes use of data analysis in research and teaching • Website is at http://www.ssric.org

  5. Social Science Data Bases • The SSRIC helps maintain and promote the use of the social science data bases in the CSU • Data bases include: • Inter-university Consortium for Political and Social Research (ICPSR) • The Field Institute • The Roper Center for Public Opinion Research • We’ll explore these data bases and how to use them at the workshop tomorrow

  6. Agenda for the Introductory SPSS Workshop • Overview of SPSS • A brief tour • Transforming data • Recode • Compute • Select If • Univariate analysis • Frequencies • Descriptives • Explore • A look ahead at the intermediate workshop

  7. Overview of SPSS • SPSS is a statistical package for beginning, intermediate, and advanced data analysis • Other statistical packages include SAS and Stata • Online statistical packages that don’t require site licenses include SDA

  8. Text – SPSS for WindowsVersion 13 A Basic Tutorial • Authors: Linda Fiddler (Bakersfield), Laura Hecht (Bakersfield), Ed Nelson (Fresno), Elizabeth Nelson (Fresno), Jim Ross (Bakersfield) • Available from McGraw-Hill Custom Publishing. Call 800-338-3987 to order. Request ISBN 0-07-353671-7 • Available on the web at http://www.csub.edu/~jross/projects/spss/. The data set for this workshop can be downloaded at this site

  9. Current Version of SPSS • Current version is 14.0 • Text is for version 13.0 • Text is revised every other version

  10. SPSS Files and Extensions • Portable file -- .por • Data file -- .sav • Output file -- .spo • Syntax file -- .sps

  11. Opening SPSS • Go to start and find SPSS for Windows • Click on SPSS 13.0 for Windows to open • You’ll need to update your SPSS license every year (or your school technician will do it for you)

  12. Creating Your Own Data File • We’re not going to go through how you would create your own data file. It would take too long. But you can go to ch. 2 in the text for a thorough discussion. (Note: the slides for creating your own data file are “hidden” in this PowerPoint presentation.) • It involves creating: • Variable names • Variable labels • Value labels • Missing values

  13. Opening an Existing File • Usually you will want to open a data set that you got from someplace else such as: • ICPSR • Field Institute • Roper Center • These files will usually be in the form of a: • SPSS portable file • SPSS data file • Raw data file with a SPSS syntax file • Raw data file without a syntax file

  14. Opening a Portable file • Click on the open yellow folder to open a new file • Change file type to .por • Browse to where the portable file you want to open is located and double click on that file

  15. Opening a Data File • Click on the open yellow folder to open a new file • Change file type to .sav • Browse to where the data file you want to open is located and double click on that file • We’re going to use the data set that comes with the text – gss02a.sav. You can download it from the web site that has the text -- http://www.csub.edu/~jross/projects/spss/

  16. Opening a Raw Data File with a SPSS Syntax File • Sometimes you will need to open a raw data file (ASCII or text) and there will be an accompanying SPSS syntax file • You will need to modify the “File Handle” and “Save Outfile” commands • See http://www.icpsr.umich.edu/help/newuser.html#05 for more information • You may need help doing this. Feel free to contact your campus SSRIC representatives or the facilitators for this workshop

  17. Opening a Raw Data File Without a SPSS Syntax File • If you don’t have a SPSS syntax file you will have to use the codebook that came with the data and create your own syntax file • You may need help doing this. Feel free to contact your campus SSRIC representatives or the facilitators for this workshop

  18. What’s Next? • Now you know how to open an existing SPSS portable or data file • Let’s do a quick overview of SPSS and then we’ll learn how to transform variables

  19. A Brief Tour of SPSS(see ch. 1 in text, pp. 5-10) • Frequencies -- Analyze/Descriptive Statistics/Frequencies • Select ABANY and move it to the big box and click on OK • Crosstabs – Analyze/Descriptive Statistics/Crosstabs • Move ABANY to the “Row” box • Move SEX to the “Column” box • Click on “Cells” and select “Column” percents • Click on OK

  20. A Brief Tour Continued • Comparing means – Analyze/Compare Means/Means • Move AGEKDBRN and EDUC in the “Dependent List” box • Move SEX to the “Independent List” box • Click on OK

  21. A Brief Tour Continued • Correlations • Analyze/Correlate/Bivariate • Move EDUC, MAEDUC, and PAEDUC into the “Variables” box • Click on OK

  22. A Brief Tour Continued • Scatterplots • Graphs/Scatter/Dot • Click on “Simple Scatter” and then on “Define” • Move EDUC into the “Y axis” box • Move PAEDUC into the “X Axis” box • Click on OK

  23. Transforming Data(see ch. 3 in text) • We can transform variables by recoding which means to combine categories on an existing variable into fewer categories • We can transform variables by creating new variables out of existing variables • We can select particular cases and analyze only these cases • We can do other things like weighting cases that we’re not going to talk about in this workshop. (Note: the slides for weighting data are “hidden” in this PowerPoint presentation.)

  24. Recoding Variables • Recoding into different variables • Recoding into the same variable • We recommend recoding into different variables and not using the into same variable option

  25. Recoding into Different Variables • Click on “Transform” and then on “Recode” and then on “into different variables” • Select the variable you want to recode • Start by giving the new variable a new name and assigning a variable label to the new variable. Click on “Change”

  26. Recoding AGE into AGE1 • Recode AGE into four categories and give it the name of AGE1 • Click on “Old and New Values” • Use “Range” (fourth option down) to recode as follows. Remember to click on “Add” after entering each recode • 18 to 29 = 1 • 30 to 49 = 2 • 50 to 69 = 3 • 70 to 89 = 4

  27. Recoding Options • When you click on “Old and New Values” there will be seven options • For most recoding you will only have to use two of these options • The first option from the top allows you to recode a single value into a new value • The fourth option from the top allows you to recode a range of values from X to Y into a new value

  28. Assign Value Labels to the Four Categories of AGE1 • Go into “Variable View” • Find the variable AGE1 (should be at the bottom of the list of variables) • Click in the “Values” column and then click on the small gray box • Enter the value labels • Click on OK

  29. Exercises for Recoding • INCOME98 is total family income. Do a frequency distribution to see what it looks like before recoding • Recode into 4 categories and call this new variable INCOME1. Use the following categories: under $20K, $20K to under $40K, $40K to under $60K, and $60K and over • Add the value labels • Run a frequency distribution for INCOME1 and check to make sure that you recoded it correctly by comparing the unrecoded and recoded frequency distributions

  30. More Exercises for Recoding • Now recode INCOME98 again and call the new variable INCOME2 • This time use 8 categories: under $10K, $10K to under $20K, $20K to under $30K, $30K to under $40K, $40K to under $50K, $50K to under $60K, $60K to under $75K, and $75K and over • Add the value labels • Run a frequency distribution for INCOME2 and check to make sure that you recoded it correctly by comparing the unrecoded and recoded frequency distributions

  31. Creating a New Variable with Compute • Let’s create a new variable and call it ABORTION which is the sum of the seven abortion variables • Click on “Transform” and then on “Compute” • Enter the new variable name (ABORTION) into the target variable box • Enter the formula for this new variable into the “Numeric Expression” box • Click on OK

  32. Dealing with Missing Data • If there is missing data for any of these variables (ABANY to ABSINGLE), the new variable ABORTION will be assigned a system missing value • What do we do if we want to allow no more than two missing values? • Let’s compute the mean value and divide the sum of the abortion values by the number of cases with valid information • But let’s allow only two variables with missing values

  33. Dealing with Missing Data Continued • Click on “Reset” to erase what is currently in the “Compute Variable” box • Click on “Statistical” in the “Function Group” box • Then double click on “Mean” in the “Function and Special Variables” box • In the “Target Variable” box, enter the name of the new variable. Let’s call it ABORMEAN • In the “Numeric Expression” box, you should see “MEAN(?,?)”

  34. Dealing with Missing Data Continued • Replace the “?,?” with the variables you want to include so it reads “MEAN (abany,abdefect,abhlth,abnomore,abpoor,abrape,absingle)” • Insert .5 following MEAN so it reads “Mean.5”. This indicates that you want to have at least five variables with valid information • Click on OK

  35. Exercises for Compute • There are five variables that measure tolerance for letting someone speak in your community who may have different views than your own: SPKATH, SPKCOM, SPKHOMO, SPKMIL, and SPKRAC • For each of these variables, 1 means they would allow such a person to speak and 2 means they would not allow it

  36. Exercises for Compute Continued • Create a new variable (call it SPEAK) which is the sum of these five variables • Run a frequency distribution for SPEAK • What do the values in this new variable tell us?

  37. More Exercises for Compute • Now let’s create a variable called SPKMEAN which allows for one of the five variables (SPKATH to SPKRAC) to be missing • What happens if there is more than one variable with a missing value? • How does SPSS calculate the new variable if there is only one variable with a missing value?

  38. Using Select Cases to Select Specific Cases for Analysis • Let’s select only Protestants for further analysis • Click on “Data” and then on “Select Cases” • Click on “If condition is satisfied” and then on the “If” button below it • Select the variable RELIG and move it into the box on the right • In this box, enter the expression “relig = 1” • Click on “Continue” and on OK

  39. Using Select Cases Continued • Now lets select Protestants who are under 35 years age old • Enter the expression “relig = 1” as you did before. • Use & for and. Enter “age < 35” so the expression reads “relig = 1 & age < 35” • Click on OK

  40. Exercises for Select If • Select all males (1 on the variable SEX) and do a frequency distribution for the variable FEAR (afraid to walk alone at night in the neighborhood) • Now select all females (2 on the variable SEX) and fun a frequency distribution for FEAR • Are males or females more fearful of walking alone at night?

  41. More Exercises for Select If • Now let’s select males under age 35 and run a frequency distribution for FEAR • Do the same thing for females under 35 • Are males or females under 35 more fearful of walking alone at night?

  42. Important Note on Using Select Cases • When you are finished using “Select Cases” and want to revert to using all the cases be sure to click on Data/Select Cases and select “All cases”. Then click on OK • If you don’t do this, you will continue to use only those cases you last selected

  43. Univariate Analysis • Now that we know how to open existing files and transform variables, we’re ready to begin analyzing data • Univariate analysis refers to analyzing variables one-at-a-time

  44. Types of Univariate Analysis Procedures (see ch. 4 in text) • Frequencies • Descriptives • Explore

  45. Frequencies • Go to Analyze/Descriptive Statistics/Frequencies • Select ABANY and AGE and click on OK

  46. Bar Charts • Bar charts – click on Analyze/Descriptive Statistics/Frequencies • Click on “Charts” • Select “Bar Charts” and click on “Continue” and then on OK • Do you think bar charts are appropriate for both ABANY and AGE?

  47. Histograms • Click on click on Analyze/Descriptive Statistics/Frequencies • Click on “Charts” • Select “Histograms” and click on “Continue” and then on OK • Do you think histograms are appropriate for both ABANY and AGE? • Which do you think is the most appropriate chart (bar chart or histogram) for ABANY and for AGE?

  48. Statistics • Click on Analyze/Descriptive Statistics/Frequencies • Click on “Statistics” • Select the statistics you want and click on “Continue” and then on OK

  49. Exercises for Frequencies • There are seven variables dealing with abortion: ABANY, ABDEFECT, ABHLTH ABNOMORE, ABPOOR, ABRAPE, and ABSINGLE • Run a frequency distribution for each variable • Get a bar chart for each variable • Compare and contrast how people answered these seven questions

  50. More Exercises for Frequencies • Run the frequency distribution for AGE • Get a histogram for AGE • Compute the following statistics for AGE: • Mean • Median • Standard deviation • Percentiles – 25th, 50th, and 75th

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