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Introductory Workshop SPSS

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Title: Introductory Workshop SPSS


1
Introductory WorkshopSPSS
  • CSU Bakersfield
  • April 17, 2009

2
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

3
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

4
Agenda for the Introductory SPSS Workshop
  • Overview of SPSS
  • A brief tour
  • Creating youre 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

5
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 dont require
    site licenses include SDA

6
Text SPSS for WindowsVersion 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 800-338-3987 to order. Request ISBN
    0-07-353833-7
  • Available on the web at http//www.ssric.org/trd/s
    pss16. The data set for this workshop can be
    downloaded at this site

7
SPSS Files and Extensions
  • Portable file -- .por
  • Data file -- .sav
  • Output file -- .spo
  • Syntax file -- .sps

8
Opening SPSS
  • Go to start and find SPSS for Windows
  • Click on SPSS 16.0 or 17.0 for Windows to open
  • Youll need to update your SPSS license every
    year (or your school technician will do it for
    you)

9
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

10
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

11
A Brief Tour Continued
  • Correlations
  • Analyze/Correlate/Bivariate
  • Move EDUC, MAEDUC, and PAEDUC into the
    Variables box
  • Click on OK

12
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

13
Creating Your Own SPSS Data File(see ch. 2 in
text)
  • Involves creating
  • Variable names
  • Variable labels
  • Value labels
  • Missing values

14
Creating a Data File in SPSS
  • Questions (see p. 11)
  • Age
  • Sex
  • Religious preference
  • Type of marriage preferred
  • Opinion on abortion (7 different questions)

15
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

16
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
    well 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

17
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

18
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

19
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

20
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 didnt make any data entry
    errors
  • Congratulations!! you created a SPSS data file.
    You could also enter the data using a
    spreadsheet like Excel

21
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 floppy
    or flashdrive

22
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

23
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

24
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
  • Were 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 --
    http//www.ssric.org/tr/onlinetextbooks. Look
    for the text Right click here to download
    GSS06A.

25
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/00
    62.xml for more information
  • You may need help doing this. Feel free to
    contact me for help

26
Opening a Raw Data File Without a SPSS Syntax
File
  • If you dont 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

27
Whats Next?
  • Now you know how to create a SPSS data file and
    how to open an existing SPSS portable or data
    file
  • Next well learn how to transform variables

28
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
    were not going to talk about in this workshop.

29
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

30
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

31
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

32
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

33
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

34
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

35
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

36
Creating a New Variable with Compute
  • Lets 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

37
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?
  • Lets compute the mean value and divide the sum
    of the abortion values by the number of cases
    with valid information
  • But lets allow only two variables with missing
    values

38
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. Lets call it ABORMEAN
  • In the Numeric Expression box, you should see
    MEAN(?,?)

39
Dealing with Missing Data Continued
  • Replace the ?,? with the variables you want to
    include so it reads MEAN (abany,abdefect,abhlth,a
    bnomore,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

40
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

41
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?

42
More Exercises for Compute
  • Now lets 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?

43
Using Select Cases to Select Specific Cases for
Analysis
  • Lets 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

44
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 lt 35 so the
    expression reads relig 1 age lt 35
  • Click on OK

45
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?

46
More Exercises for Select If
  • Now lets 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?

47
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 dont do this, you will continue to use
    only those cases you last selected

48
Univariate Analysis
  • Now that we know how to open existing files and
    transform variables, were ready to begin
    analyzing data
  • Univariate analysis refers to analyzing variables
    one-at-a-time

49
Types of Univariate Analysis Procedures (see
ch. 4 in text)
  • Frequencies
  • Descriptives
  • Explore

50
Frequencies
  • Go to Analyze/Descriptive Statistics/Frequencies
  • Select ABANY and AGE and click on OK

51
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?

52
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?

53
Statistics
  • Click on Analyze/Descriptive Statistics/Frequencie
    s
  • Click on Statistics
  • Select the statistics you want and click on
    Continue and then on OK

54
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

55
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

56
Descriptives
  • Click on Analyze/Descriptive Statistics/Descriptiv
    es
  • Select AGE and EDUC
  • Click on Options and select the statistics you
    want and then click on Continue and OK

57
Exercises for Descriptives
  • Use Descriptives to compute the following
    statistics for AGE
  • Mean
  • Standard deviation
  • Variance
  • Skewness
  • Kurtosis

58
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?

59
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

60
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

61
Selecting Plots for Explore
  • Click on Plots
  • Select the plots you want
  • Click on Continue and then OK

62
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
  • Whats the difference?

63
Intermediate Workshop for SPSS
  • In the next workshop well 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)
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