Introductory Workshop SPSS CSU Fresno March 12, 2010

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 Promotes use of data analysis in research and teaching Website is at

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

Agenda for the Introductory SPSS Workshop Overview of SPSS A brief tour Creating you’re your own SPSS data file or opening a data file you got somewhere else Transforming data –Recode –Compute –Select If Univariate analysis –Frequencies –Descriptives –Explore A look ahead at the intermediate workshop – March 15 from 9:00 am to noon

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 16 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 to order. Request ISBN Available on the web at The data set for this workshop can be downloaded at this site

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 16.0 to open You’ll need to update your SPSS license every year (or your school technician will do it for you)

A Brief Tour of SPSS (see ch. 1 in text) 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/Legacy Dialogs/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

Creating Your Own SPSS Data File (see ch. 2 in text) Involves creating: –Variable names –Variable labels –Value labels –Missing values

Creating a Data File in SPSS Questions (see p. 11) –Age –Sex –Religious preference –Political views –Type of marriage preferred –Opinion on abortion (7 different questions)

Basic Steps in Creating a Data File Assign identification number to each case Assign each variable a variable name and an extended variable label Each variable will have a set of values. Assign each value an extended value label If a variable has missing information, decide which values will be used as the missing values

Variable Names Traditionally variable names had to be 8 characters or less, start with a letter, and contain no embedded blanks Now they can be longer than 8 characters, but we’ll stick with names of 8 or fewer characters Names can contain some special characters, but not all such characters. So we only use hyphens (-) as special characters in names

Variable Names Age is named AGE Sex is named SEX Religious preference is named REL Political orientation is named C-L Preferred marriage is named MG There are seven abortion variables and they are named ABD, ABN, ABH, ABP, ABR, ABS, ABA

Entering the Information for a Data File You already have SPSS open Click on File/New/Data You should see a blank data screen that looks like a spreadsheet At the bottom are two tabs called “Data View” and “Variable View”. Click on “Variable View”

Defining the Variables Enter the variable names in the “Names” columns in the order you want them Enter the variable labels in the “Label” column Enter the value labels in the “Values” column. To do this you will need to click in the appropriate cell and then click in the little gray box on the right Enter the missing values in the “Missing” column. To do this you will need to click in the appropriate cell and then click in the little gray box on the right

Adding in the Data Now that you have defined the variables, click on the tab at the bottom called “Data View” and enter the data into the appropriate cells. The data are on p. 18 of the text Once you have entered the data, go back and check to make sure you didn’t make any data entry errors Congratulations!! – you created a SPSS data file. You could also enter the data using a spreadsheet like Excel

Saving the Data File Now you want to save your data file Click on “Save as”. The default is to save it as a SPSS data file with.sav as the extension Give it a file name and indicate where you want to save it on your hard drive or on your flashdrive

Opening an Existing File You Got Somewhere Else Often 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 (.por) –SPSS data file (.sav) –Raw data file with a SPSS syntax file (.sps) –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 an SPSS 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 – gss06a.sav. You can download it from the web site that has the text -- Look for the text – “Right click here to download GSS06A.”

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 and xml for more information xml You may need help doing this. Feel free to contact me for help

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 me for help

Choosing Options in SPSS Click on “Edit” and “Options.” General tab -- under “Variable Lists,” check “Display Names” and “Alphabetical.” Output Labels tab -- select “Names and Labels” in the first box, and “Values and Labels” in the second.

What’s Next? Now you know how to create a SPSS data file and how to open an existing SPSS portable or data file Next we’ll learn how to transform variables

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.

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 INCOME06 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 INCOME06 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)