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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 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
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 Mc. Graw-Hill Custom Publishing. Call 800 -338 -3987 to order. Request ISBN 0 -07353833 -7 • Available on the web at http: //www. ssric. org/trd/spss 16. 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 – gss 06 a. sav. You can download it from the web site that has the text -- http: //www. ssric. org/tr/onlinetextbooks. Look for the text – “Right click here to download GSS 06 A. ”
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. ssric. org/files/ASCII_to_SPSS. pdf and http: //www. icpsr. umich. edu/cocoon/ICPSR/FAQ/ 0062. xml for more information • 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 AGE 1 • Recode AGE into four categories and give it the name of AGE 1 – 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 AGE 1 • Go into “Variable View” • Find the variable AGE 1 (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 • INCOME 06 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 INCOME 1. Use the following categories: under $20 K, $20 K to under $40 K, $40 K to under $60 K, and $60 K and over • Add the value labels • Run a frequency distribution for INCOME 1 and check to make sure that you recoded it correctly by comparing the unrecoded and recoded frequency distributions
More Exercises for Recoding • Now recode INCOME 06 again and call the new variable INCOME 2 • This time use 8 categories: under $10 K, $10 K to under $20 K, $20 K to under $30 K, $30 K to under $40 K, $40 K to under $50 K, $50 K to under $60 K, $60 K to under $75 K, and $75 K and over • Add the value labels • Run a frequency distribution for INCOME 2 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)