This document provides instructions for analyzing the relationship between two variables using cross tabulation in SPSS. It discusses identifying independent and dependent variables, creating cross tabs by moving variables to column and row positions, calculating column percentages to compare groups, and determining if a relationship exists based on differences in percentages between groups. Examples are provided to demonstrate how to interpret cross tabs and determine if one group is more or less likely than another to have a characteristic.

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1
Problem 1: Relationship between Two
Variables-1 (1)
First, identify two variables with which this
question is related. Here, the variables of
interest are [attend] and [sex].
Second, examine the direction of relationship. In
other words, for example, examine whether female
were “more” or “less” likely to attend religious
services more than once a week than male.

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Problem 1: Relationship between Two
Variables-1 (2)
Furthermore, by now, you should be able
to identify that [sex] is an independent
variable and [attend] is a dependent
variable in this statement.
Now, let’s explore how to answer this
question using SPSS.

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3 Cross Tabulation in SPSS-1 (1)
Recall that the cross tabulation is a way to examine
the relationship between two variables. In SPSS, you
can get a cross tabulation in
Analyze > Descriptive Statistics >
Crosstabs…
In other words, click on Analyze in the menu bar,
select Descriptive Statistics, then Crosstabs…

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4 Cross Tabulation in SPSS-1 (2)
In the Crosstabs window, find and move the
independent and dependent variable to
Column(s): and Row(s): boxes, respectively. In
this case, the independent variable [sex] goes to
Column(s): box and the dependent variable
[attend] goes to Row(s): box.

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5 Cross Tabulation in SPSS-1 (3)
Next, click on the Cells…
button to get percentage
values for each cell in
the cross tabulation.

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6 Cross Tabulation in SPSS-1 (4)
In the Cell Display window, select the Column in the
Percentages section. It allows you to have percentage value
separately calculated for each category of the independent
variable. Make sure that Observed was selected in the Counts
section although it should be checked by default.
Click on Continue and OK buttons to see the cross tabulation.

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7 Cross Tabulation in SPSS-1 (5)
The output displays two
tables, one for case
processing summary
and the other for cross
tabulation of the two
variables. Notice that
[sex] is on the column
and [attend] is on the
row of the cross
tabulation as we
assigned.

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8 Cross Tabulation in SPSS-1 (6)
Also notice that the percentage
values were calculated by column
(i.e., [sex]). For example, the
percentage value on the row
labeled “8 MORE THAN ONCE
WK”, “% within RESPONDENTS
SEX”, in the column labeled “1
MALE” was obtained with the
count of the cell (18) divided by
the count of the males (291) (i.e.
18/291=6.2%). In other words,
6.2% of male respondents said
that they attended religious
services more than once a week.

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9 Cross Tabulation in SPSS-1 (7)
While 6.2% of male
respondents, or 18 out of 291
males, said that they attended
religious services more than
once a week, 9.3% of female
respondents, or 35 out of 375
females, said that they
attended religious services
more than once a week.
Thus, we can conclude that
female respondents were
more likely to have said that
they attended religious
services more than once a
week than male.

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10 Cross Tabulation in SPSS-1 (8)
Using the frequency for each
category (i.e., male, female) to
compare the likelihood of a
specific answer can be
misleading. At the row labeled
“0 NEVER”, for example, more
female respondents (56) said
that they have never attended
religious services than males
(53), which sounds true when
we simply look at the counts.
However, when we compare
the % within respondents’ sex
the relationship becomes
reverse and males (18.2%)
are more likely to say that they
have never attended religious
services than females
(14.9%).

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11
Problem 2: Relationship between Two
Variables-2
This question is asking
whether there is a
relationship between
[sex] and [ethimp].
Again, you have to
know that [sex] is an
independent variable
and [ethimp] is a
dependent variable
here.

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12 Cross Tabulation in SPSS-2 (1)
Recall that you can get a cross tabulation in
Analyze > Descriptive Statistics >
Crosstabs…
In other words, click on Analyze in the menu bar,
select Descriptive Statistics, then Crosstabs…

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13 Cross Tabulation in SPSS-2 (2)
First, in the Crosstabs window,
find and move the independent
variable [sex] to Column(s): box
and the dependent variable
[ethimp] to Row(s): box.
Next, click Cells… button and
select Columns in Percentages
section.

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14 Cross Tabulation in SPSS-2 (3)
Make sure that Observed in
Counts section and Column
in Percentages section were
selected. Then click
Continue and OK buttons to
get the crosstab.

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15 Cross Tabulation in SPSS-2 (4)
We can say that a relationship
exists between two variables in
a bivariate table if the groups
defined by the independent
variable have differences of
10% or more in the categories
of the dependent variable. In
this case, the largest difference
in the column percentages for
survey respondents in the
categories of "importance of
ethnic identity" when compared
across the groups defined by
"sex" (male and female) was
that of “3 Moderately
Important”, which was 3.5%
(=28.0-24.5). Thus no
relationship exists between two
variables.

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16
Problem 3: Relationship between Two
Variables-3 (1)
This question asks about how much is the relationship
between the two variables. Notice that the dependent
variable in this question is [ethtrads] and the independent
variable is [sex].

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17 Cross Tabulation in SPSS-3 (1)
The cross tabulation shows
that 32% of female and 26%
of male respondents have
said that they strongly agree
that each ethnic group has
the right to maintain its unique
traditions. In other words,
female were about one and a
quarter times
(32.0/26.0=1.23) more likely
to have said they strongly
agreed that each ethnic group
has the right to maintain its
unique traditions than survey
respondents who were male.

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18 Steps in solving crosstabulation problems - 1
Question: is group defined by independent variable more (less)
likely to have dependent variable characteristic?
False
Is the column percentage in
the dependent variable
category larger (smaller) for
the more (less) likely group?
No
True
Yes
Create cross-tabulated table in SPSS with
independent variable as the column variable
and the dependent as the row variable.
Include column percentages.
NOTE: when the
column percentages
are very similar, we
can say the groups
are about equally
likely.

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19 Steps in solving crosstabulation problems - 2
Question: is there a relationship between the independent and
the dependent variable?
False
Differences in the column
percentages equal to or larger
than 10% in any category of
the dependent variable
(ignoring rows or columns with
fewer than 10 subjects)?
No
True
Yes
Create cross-tabulated table in SPSS with
independent variable as the column variable
and the dependent as the row variable.
Include column percentages.
When a problem includes
two variables, but does
not identify the role of
either one, treat the first
mentioned variable as
the independent variable.

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20 Steps in solving crosstabulation problems - 3
Question: is group defined by independent variable ? times more
likely to have dependent variable characteristic?
False
Is the percent in the
independent variable category
for the more likely group ÷ the
percent for the less like group
equal to the correct ratio?
No
True
Yes
Create cross-tabulated table in SPSS with
independent variable as the column variable
and the dependent as the row variable.
Include column percentages.