# SPSS WORKSHOP by IFY9nc7Y

VIEWS: 10 PAGES: 36

• pg 1
```									         SPSS WORKSHOP 
User Name: type in your user ID
If you have trouble signing in:
– Then try signing in with westguest account
User Name: westguest
Domain: (this computer)
–Sometime after today’s class, please go to
Technopolis (basement of library) to get your user ID
fixed.
Brief Introduction to
Statistics with SPSS
Roger Berger
Mathematical Sciences &
Applied Computing Department

Rico Rivera
Josh Fox
Heather Ohton
Tommy Aguila
Christopher Zambakari
Statistics Laboratory
http://www.west.asu.edu/StatLab
Workshop Overview
• Workshop Objectives (p 1)
–   Overview of Basic Organization of SPSS
–   How to input raw data
–   How raw data file is edited in “variable view”
–   Perform basic data analyses

http://www.west.asu.edu/StatLab
• Click on Workshops
• Click on Data Used for SPSS Workshops
• Click on Res_Stat_Edited_Data.sav
• Please do not open the data file
• Close the internet brower.

Click on My Network Places
• Click on \\westfile\web\CGIWEB\statlab
• Click on WorkshopExample.sav (SPSS file)
• Click on WorkshopExample.xls (Excel file)
• Please do not open the data file
SPSS Accessibility (p. 3)
• Network access
– Technopolis (basement of library)
• Desktop (hard drive) installed
– Computer Classrooms
– Stat Lab
Accessing the Statistic Laboratory
(p. 3)

• Location: CLCC 107
• Phone: (602) 543-6117
• Website: http://www.west.asu.edu/StatLab
• Operating hours: See website (changes on a
weekly basis)
front counter
Support for Statistics (p. 4)
• Function of Stat Lab
– The Stat Lab staff assists students with aspects of
statistical software.
– The Stat Lab is not set up to provide one-on-one
tutorial service for students on a regular basis.
– However, we have and frequently do answer general
statistic questions.
• Statistics Tutoring (bottom of p 4)
– Learning Enhancement Center
– TRiO (SSS) program
Procedures for Data Analysis (p. 6)

Data  Statistics Software  Output  Interpretation

1.   Collect & organize data
2.   Input & edit the data
3.   Analyze data or create graphs
4.   State results and interpret
Please fill out the Research & Statistics Attitude Survey
(Remove the last page of your handout)
• Response
– Strongly Disagree = 1
– Disagree = 2
– Agree = 3
– Strongly Agree = 4
• Sex
– Male = 1
– Female = 2
• Age
– Under 25 = 1
– 25 – 40 = 2
– Over 40 = 3
cases
• What do the first 5 questions (items) measure?
• What do items 6 through 10 measure?
Let’s Launch SPSS
– Data & Transform are used to manipulate the data in
– Analyze and Graphs are used to create output
• Tabs (bottom left hand corner of data editor, p. 7)
– Data View
• Columns: Variables (e.g., questions on survey)
• Rows: Cases (e.g., survey)
– Variable View
• How we edit the variables
• Give variables their names, labels, etc
• Enter you survey into Data View
Editing the Raw Data
• Variable View
– Tab (located lower left hand corner)
– Pages 9 – 10 of your handout
Retrieving an Edited Data
• Save the data set to your desktop.
• Call it “edited data” & your initials
– E.g., editeddataRR
• Now we are going to open up a new data
set.
• File > open > Data
from our website.
Review of Workshop
• We inputted raw data (from the survey)
into the data editor

• We edited a raw data file in “variable view”
– pp. 9 - 10

• We retrieved an edited file and perform
some basic statistical analyses.
Two Topics
• Prepping an Excel spreadsheet to be
imported into SPSS

• Types of Analyses of variance (ANOVA).
•   Each column is indicative of a
variable
•   First row contains the variable
names
•   You want to keep the same rules
that apply to variable names in
SPSS
•   The subsequent rows contain the
data for each case (subject)
•   Gender has two levels
–   Male = 1
–   Female = 2
•   Age has three levels
–   < 25 = 1
–   25 - 40 = 2
–   > 40 = 3
•   Time has three levels
–   Baseline = time0
–   Time 1 = time1
–   Time 2 = time2
•   Composite scores for “attitude
towards research”

I sorted the data based on
gender and age
variables for
instructional purposes.
Between subjects (aka
independent
samples)
• What are two
between-subject
factors that have
independent
samples?
– Gender: 2 samples
– Age: 3 samples

Within subjects (aka
related samples)
• What is the one
within-subject factor
that is indicative of
three related
samples?
– Time: 3 samples
Importing Excel Data into SPSS
Stat Lab Staff: you may want to print this slide and follow the SPSS directions below

•    After formatting the data in Excel
– First row contains the variable names
– Other rows contain the data values
•    Save and close Excel file
•    Open up SPSS
– Click on File > Open > Data
– Navigate to the location you save the Excel file
– In “Files of type:” choose either
• Excel (*.xls)
• or All files (*.*)
• Open the Excel file you saved
– You’ll get a dialogue box called: Opening Excel Data Source
• There is a green check mark in box: Read variable names from the list from the first row
of data
• Worksheet: choose the worksheet in which the data is located
• Click the OK button.
– You just imported an excel file into SPSS
Analysis of Variance
• One-way ANOVA
– One between subjects factor
– Example: Age
• Two-way ANOVA
– Usually consist of two between subjects factors
– Example: Age and Gender
• Repeated Measures
– One-way within subjects ANOVA
• One within subjects factor
• Example: Time
– Two-way between and within subjects ANOVA
• One between subjects factor (e.g., Time)
• And one within subject factor (e.g., Age)
One-way ANOVA
You may want to open the SPSS data file that you downloaded.

•   Differences among 2 or more independent sample means with SPSS
• Analysis of Variance
•   Analyze > Compare Means > One-Way ANOVA …
•   One dependent variable (e.g., baseline, time0) goes into the “Dependent List:”
•   One between subjects factor (e.g., Age) goes into “Factor:”
•   If the factor has more than three level, click on Post Hoc…
– Click on Tukey and Dunett’s C (unless your instructor wants you to use a
different one).
– Click on continue
•   Click on Options
– Chose
• descriptive Statistics
• Homogeneity of variance test
• Perhaps on Means plot
– Click on continue
•   Click on OK
Descriptive Statistics
Des criptives

time0
95% Conf idence Interval f or
Mean
N        Mean     Std. Deviation   Std. Error   Low er Bound Upper Bound         Minimum    Max imum
Under 25        33    14.12           3.267          .569          12.96           15.28            7          20
25 - 40         37    13.24           3.840          .631          11.96           14.52            7          20
Over 40         25     9.76           3.018          .604           8.51           11.01            6          18
Total           95    12.63           3.837          .394          11.85           13.41            6          20

• The first columns contains the three levels of the Age factor.
• The mean column contains the mean “attitude toward statistics”
•Does it appear that there may be an age effect?
•Do you notice a trend?
•Which age group has the greatest mean?
F-test

ANOVA

time0
Sum of
Squares     df        Mean Square    F       Sig.
Betw een Groups    293.219          2       146.610   12.364     .000
Within Groups     1090.886         92        11.857
Total             1384.105         94

•   The F-test looks tells us if there is an age effect.
•   Is the F-test significant?
– Look at the p value (in column called Sig.)
– Is it less than an alpha of .05?
•   However, the F-test does not tell us which pair of means are significantly
different.
•   We look at the multiple comparisons for that.
Multiple Comparisons
Multiple Com parisons

Dependent V ariable: time0

Mean
Dif f erence                           95% Conf idence Interval
(I) age       (J) age             (I-J)     Std. Error   Sig.     Low er Bound Upper Bound
Tukey HSD      Under 25      25 - 40                 .878        .824     .538           -1.09           2.84
Over 40                4.361*       .913     .000            2.19           6.54
25 - 40       Under 25               -.878        .824     .538           -2.84           1.09
Over 40                3.483*       .891     .001            1.36           5.61
Over 40       Under 25              -4.361*       .913     .000           -6.54          -2.19
25 - 40               -3.483*       .891     .001           -5.61          -1.36
Dunnett C      Under 25      25 - 40                 .878        .850                    -1.20           2.96
Over 40                4.361*       .829                     2.31           6.42
25 - 40       Under 25               -.878        .850                    -2.96           1.20
Over 40                3.483*       .873                     1.33           5.64
Over 40       Under 25              -4.361*       .829                    -6.42          -2.31
25 - 40               -3.483*       .873                    -5.64          -1.33
*. The mean dif f erenc e is s ignif icant at the .05 lev el.

•Mean difference column was calculated by subtracting the means
for age categories in column (j) from means for age categories in
column (I).
•If there is an asterisk, the mean difference is significant.
Two-way ANOVA
• Analyze > General Linear Model >
Univariate…
• Dialogue box titled Univariate
– Dependent variable: move one dependent
variable (e.g., baseline: time0)
– Fixed Factor(s): move in the between subjects
factors (e.g., Gender and Age).
Dialogue box titled Univariate
(continued)
• Click on Plots
– Move one of factors into horizontal axis and
the other into separate lines
– If you wish, you can do the inverse of that,
– Click Continue
Dialogue box titled Univariate
(continued)
• Click on Post Hoc…
– Choose only factors that have three or more
levels. (e.g., Age).
– Click on Tukey and Dunett’s C (unless your instructor
wants you to use different ones).
– Click on continue
Dialogue box titled Univariate
(continued)
• Click on Option…
– Choose Descriptive statistics
– Homogeneity tests
– Click on continue
• Click on OK
Repeated Measures
• Analyze > General Linear Model > Repeated
Measures…
• Dialogue box: Repeated Measures Define
Factor(s)
• Within-Subject Factor Name:
– Change name to: time
– Number of levels: 3 levels (i.e., baseline, time0, and
time1)
– Click on Define
Dialogue Box: Repeated Measures
• Within-Subjects Variables (time):
– Choose the three variables (time0, time1,
time2) the insert them in the correct order.
– Between-Subjects Factor(s):
• Insert the factors that you are interested in.
• In this case, enter in Age.
Dialogue Box: Repeated Measures
(continued)
• Click on Plots
– I recommend that you move the Time factor
into horizontal axis and the other (Age) into
separate lines
– Click Continue
Dialogue Box: Repeated Measures
(continued)
• Click on Post Hoc…
– Choose only factor(s) that have three or more
levels. (e.g., Age).
– Click on Tukey and Dunett’s C (unless your instructor
wants you to use different ones).
– Click on continue
Dialogue Box: Repeated Measures
(continued)
• Click on Option…
– Choose Descriptive statistics
– Homogeneity tests
– Click on continue
• Click on OK
Stat Lab Resources
• 12 PC computers, printer (free printing), and copier
(limited use)
• Office supplies (stapler, 3-hole puncher, paper clips)
• Reference library (books can not leave the Stat Lab):
– Introductory text books on Statistics & Research Methods
– Publication manual of the American Psychological
Association
– Presenting your findings: a practical guide for creating
tables
– Displaying your findings: a practical guide for creating
figures, posters, and presentations
– Using SPSS for Windows & Macintosh: analyzing &
understanding data analyses (helpful in interpreting the
results and writing it in APA format)
Thanks for having us as your guests 

We have to justify the Stat Lab conducting
SPSS workshops.

Could you please fill out the “SPSS workshop
Evaluation” at last page of the packet.

• what you like most of the workshop,
• what you have learned about the workshop,
• how we may be able to improve it.
We will greatly appreciate it.

Thank You,
Thanks for having us as your guests 

Do keep the “Research and Statistics Attitude
Survey” you filled out.

Please turn in the “SPSS Workshop
Evaluation.” You can drop off this evaluation
near the door.