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 [email protected]

• Jim Ross – CSU Bakersfield [email protected]

• Campus representatives for the Social Sciences Research and Instructional Council (SSRIC)

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

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

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

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

Text – SPSS for Windows Version 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

Current Version of SPSS

• Current version is 14.0

• Text is for version 13.0

• Text is revised every other version

SPSS Files and Extensions

• Portable file -- .por

• Data file -- .sav

• Output file -- .spo

• Syntax file -- .sps

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)

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

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

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

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/

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#0 5 for more information • You may need help doing this. Feel free to contact your campus SSRIC representatives or the facilitators for this workshop

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

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

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

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

A Brief Tour Continued

• Correlations – Analyze/Correlate/Bivariate – Move EDUC, MAEDUC, and PAEDUC into the “Variables” box – Click on OK

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

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.)

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

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”

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

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

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

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

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

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

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

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(?,?)”

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

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

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?

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?

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

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

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?

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?

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

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

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

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

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?

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?

Statistics

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

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

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 – 25 th , 50 th , and 75 th

Descriptives

• Click on Analyze/Descriptive Statistics/Descriptives • Select AGE and EDUC • Click on “Options” and select the statistics you want and then click on “Continue” and OK

Exercises for Descriptives

• Use Descriptives to compute the following statistics for AGE – Mean – Standard deviation – Variance – Skewness – Kurtosis

More Exercises for Descriptives • Use Descriptives to compute the mean for EDUC, MAEDUC, PAEDUC • Who has the most education – respondents or their parents?

• Who has the most education – mothers or fathers?

Explore

• Click on Analyze/Descriptive Statistics/Explore • Select EDUC and put it in the “Dependent List” • In the Display box on the lower left, click on “Both” • Click on OK

Selecting Statistics for Explore

• Click on Analyze/Descriptive Statistics/Explore • Click on “Statistics” and select the statistics you want • Click on “Continue” and then OK

Selecting Plots for Explore

• Click on “Plots” • Select the plots you want • Click on “Continue” and then OK

Exercises for Explore

• Using Explore to get the following statistics and plots for the variables EDUC, PAEDUC, and MAEDUC – Descriptives – Outliers – Stem-and-leaf plot – Histogram – Boxplot • First select “Factor levels together” and run it • Then select “Dependents together” and run it again • What’s the difference?

Intermediate Workshop for SPSS • In the next workshop we’ll look at different types of statistical analysis you can do in SPSS – Cross tabulations (ch. 5) – Comparing means (ch. 6) – Correlation and regression (ch. 7) – Multivariate analysis (ch. 8) • Cross tabulations • Multiple regression – Presenting your data – charts and tables (ch. 9)