SPSS: Beyond the Basics
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Transcript SPSS: Beyond the Basics
SPSS: Beyond the Basics
A “next steps” class on
SPSS 16 for PCs
Consultant: Betty Zou
What we will cover:
PART 1
Open Excel files in SPSS
Merge SPSS files
Multiple Response Questions
PART 2
The Wonders of Statistics Coach
Bivariate Correlation
T-Tests
One-Sample
Independent
Paired
PART 1
Open an Excel file in SPSS
In your Excel document
Set-up should be like in SPSS
Variable names in the first row
Each row is a case
In SPSS
File > open data
Specify “Files of type”
Open:
“Beyond_ExampleData_1.xls”
(notice all the file types)
In pop-up window--specify worksheet
Merge SPSS files
Some sources will give you data sets in separate files
For example:
New Immigrant Survey: http://nis.princeton.edu/
Same respondents, different questions
Income, Assets, Employment all in separate files
Merge
Sort data in all files in ascending order
Keep one file as working file and merge into that file
Data > Merge Files > Add Variables
Match cases on key variables: “ID”
Merge: “Sample_Data_2” to “Sample_Data_Main”
Multiple response questions
Respondents might give more than
one answer to a question.
What is your favorite beer?
a. PBR
b. Corona
e. Budweiser
f. Other
c. Fat Tire
d. Mannies
g. Don’t drink beer
What is your favorite genre of music?
a. Hip-hop
b. Rock
c. Punk
d. Folk
e. Country
f. Other (please specify) _________
Multiple Response Questions
(cont’d)
2 Options when entering data
1. Multiple category method
(Beer 1, Beer 2, Beer 3)
2. Multiple dichotomy method
Create a variable for each answer choice
(Hip-hop, Rock, Punk…)
Enter “1” if the answer choice was chosen, “0” for not
Other (fill-in answer)
Enter data & automatic recode OR
Code the data yourself
Define Multiple Response Sets
Which beer is more popular? PBR or
Bud?
Analyze > Multiple Response > Define
Variable Sets
Set Variables Beer 1 – Beer 3
Set Variables are coded as “Categories”
Range: 1 through 7 (the value labels)
Analyze > Multiple Response >
Frequencies/ Crosstabs
More on Multiple Response
Are men or women more likely to
listen to hip-hop?
Same process as before
Set Variables are coded as “Dichotomies”
Counted Value: 1
Go to crosstabs
It may ask you to define range for “gender”
Enter 1 for Min, 2 for Max
PART 2
Statistics Coach
Help > Statistics Coach
What do you want to do?
Ex: Compare groups for significant
differences
Data in categories
Show Crosstabs Case Studies
Bivariate Correlation
Is there a correlation between age
and income?
Using dataset: “Sample_Data_Main”
2 scale variables: “age” and “income”
Analyze > Correlate > Bivariate
Check Pearson, Flag significant correlations
Interpret: Pearson (0.665), Sig (0.00)
There is a positive relationship between age and
income. The higher the age, the higher the wage.
This correlation is highly significant.
Scatter Plot
T-Test: One Sample
You know that the average number of hours people
work per week is 40.
You want to know if the average number of hours
worked in your sample is different from the known
value.
Analyze > Compare Means > One-Sample T Test
Enter “WorkHrs” ; Test value: 40
Interpret: The sample mean is 44.6750
Sig. 0.014 significant at the 5% significance level
t = 2.564
The sample mean could be 44.675 +2.564 or -2.564
These people are generally over worked
The difference is significant
T-Test: Independent
Is the average annual income of females
different from males?
You want to compare the mean of two
unrelated groups.
Analyze > Independent-Samples T Test
Test variables: Income
Grouping variables: Gender
Define Groups: 1, 2
Interpret: Sig: 0.301 The difference is not
significant.
T-Test: Paired
A soda with ginko biloba in it claims to
improve test scores.
Your sample was given a general
knowledge test before and after drinking
the soda. (Test score out of 100)
You want to test if drinking the soda
significantly improves test scores.
Use Paired because you are comparing two
measurements for the same individuals.
T-Test: Paired (cont’d)
Analyze> Paired-Samples T Test
Variable 1: PreTest
Variable 2: PostTest
Notice that you can compare more pairs
Interpret:
Drinking the soda actually reduces test
scores by an average of about 40 points!
Sig: 0.000, it is highly significant