Reading Statistics: The SPSSPC Frequencies Printout
Reading Statistics:
The SPSSPC "Frequencies" Printout
Frequencies tell you both the number and the percentage of all parents who selected each
response. Following is an example:
A19
Caused Less Angry
Frequency
Valid
Missing
Total
No
Yes
Total
System
88
121
209
6
215
Percent
40.9
56.3
97.2
2.8
100.0
Valid
Percent
42.1
57.9
100.0
Cumulative
Percent
42.1
100.0
? The column labeled "frequency" lists the actual number of parents who selected each
response. In the example, 88 parents answered "no" and 121 answered "yes."
? The column labeled "percent" lists the actual percentages of the total sample who
answered either "yes" or "no."
? "Valid percent" is the percent when missing data are excluded from the calculations.
In other words, these are the percentages of parents who selected each response after
we disregard missing responses.
? The row labeled "missing system" shows the number and the percentage of parents
who either did not answer the question, or whose answer was invalid. In the example,
6 parents gave no answer (2.8% of the total).
What numbers do you report?
? For percentages in "yes/no" questions, such as the one above from the Dane County
evaluation, report the "percent." This makes the assumption that people who didn't
answer are really giving a "no" answer. Thus we are using the total sample.
Just the "percent" of people who answered "yes" should be reported. This is how a
report of these results might read: "Over half of the parents (56%) reported that
reading the newsletter caused me to be less angry when my baby is difficult." The
bar graph (labeled "Figure 7") shows the percentage of respondents answering "yes"
to the questions of self-reported effects of reading the newsletter. The third bar
represents the 56% of "yes" respondents from the table above.
? For questions 1 - 14 you should also report the "percent" since we want to know
the percentage of the total sample who selected each response.
? For the percentages of socio-demographic variables (A24-32), you should use the
entries under the column "valid percent." Valid percent is used for these variables,
rather than percent, because we assume that the missing cases are distributed
proportionately among all the response categories. This allows us to make pie charts
that add up to 100%.
A32
Family Income
Frequency
Valid
Missing
Total
Less than 10 K
10K - 19,999
20K - 29,999
30K - 49,999
50K or more
Total
System
17
20
29
65
74
205
10
215
Percent
7.9
9.3
13.5
30.2
34.4
95.3
4.7
100.0
Valid
Percent
8.3
9.8
14.1
31.7
36.1
100.0
Cumulative
Percent
8.3
18.1
32.2
63.9
100.0
? In the frequency table above, 205 of the 215 parents had valid data, while 10 families
(4.7%) had missing data. You can see the "valid percents" are slightly higher than the
"percents" because the 10 missing cases have been removed from consideration. The
bar chart labeled "Figure 3" demonstrates how these percentages would be graphed in
the final report.
? Note that sometimes you need to do some recalculating on your own. Here is an
example from the Frequencies table above: "Two-thirds of respondents (68%)
reported their family income to be $30,000 or more per year." The 68% figure comes
from adding the valid percents from two rows (31.7 for those from 30K to 49,999 and
36.1 for those with 50K or more equals 67.8% which rounds to 68%).
? In the final report, press releases, and other public documents, we recommend
rounding percentages to the nearest whole number. We lose a little accuracy this
way, but avoid frightening math-phobic people. So we would round 14.4 to 14 and
14.6 to 15. But which way would you round 14.5? Here is the rule of thumb we
follow: round .5 to the nearest even number. Therefore, 14.5 would round down to
14, but 15.5 would round up to 16, the nearest even number. In this way there is no
systemic bias upward or downward.
Figure 3
Family Incomes, 1992
36%
$50,000 or more
32%
$30,000 to 49,999
14%
$20,000 to 29,999
10%
$10,000 to 19,999
Less than $10,000
0%
8%
10%
20%
30%
40%
Percentage of Respondents
50%
Figure 7
Self-Reported Behavior Change
"Reading the newsletters caused me to...
Provide more things for my baby
to feel, see, listen to, smell."
74%
62%
Talk to my baby more."
56%
Be less angry when my baby is difficult."
Respond more quickly when my baby cried."
Smile, kiss & hug my baby more."
0%
46%
39%
50%
100%
Percentage of Respondents
Reading Statistics:
The SPSSPC "Crosstabs" Printout
Cross-tabulations are called "crosstabs" for short, and literally tabulate one
variable across another. In the example below we have cross-tabulated parents' selfreport responses of whether reading the newsletter caused them to be less angry when
their baby was difficult with the variable called RISK2, that indicates whether a parent
could be considered as having one of six risk factors. If a parent reported being
primiparous, teenage, in a non-two parent household, low education, low income, or
isolated, then this parent was defined as at risk. Otherwise they were defined in the nonrisk group.
Every statistical software system prints out a crosstab a little differently, so don't
be surprised if you need to relearn how to read this. We'll walk you through it here.
RISK2
2-LEVEL RISK VAR * CAUSED LESS ANGRY
Crosstab
Caused Less Angry
Total
2-LEVEL
RISK VAR
NON-RISK
PRIMI AND
RISK GRP
Total
Count
% within 2-LEVEL
RISK VAR
Count
% within 2-LEVEL
RISK VAR
Count
% within 2-LEVEL
RISK VAR
No
42
Yes
34
55.3%
46
44.7%
87
100.0%
133
34.6%
65.4%
100.0%
121
88
42.1%
57.9%
76
209
100.0%
Chi-Square Tests
Value
Pearson Chi-Square
8.48214
Continuity Correction 7.65513
Df
1
1
Asymp.Sig
(2-sided)
.00359
.00566
Exact Sig
(2-sided)
Exact Sig
(1-sided)
? First, note that it tells you right at the top which two variables are being cross
tabulated (i.e. 2-LEVEL RISK VAR * CAUSED LESS ANGRY).
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