SPSS Part 2
Kin 260
Jackie Kiwata
Overview
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
Review
Comparing Sets of Data
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
Correlation
T-Tests
Overview in depth

Once data is organized, we generally analyze
the data by
Evaluating raw scores
-OR Comparing sets of data


Last time we evaluated raw scores


For instance, we calculated percentiles
Today, we’ll compare sets of data using SPSS
Statistical Significance Tests

Correlation


Basic idea: Use to determine if a relationship
exists between variables
T-tests

Basic idea: Use to determine if the means of 2
samples are statistically the same or different
Correlation Review

Indicates the extent to which two variables are related.
 The technique used to measure this is Pearson’s correlation
coefficient, r
 The closer r is to 1 or -1, the stronger the relationship
 But Pearson’s correlation coefficient does not indicate
causation
 Not correct to say X causes Y
 The strength of the relationship is classified using:
.9 or greater
strong
.8 - .9
moderately strong
.7 - .8
moderate
.5 - .7
low
< .5
no relationship
Correlation: SPSS example

Research question: Can a person’s height predict
their vertical jump height?
Height (in)
11.5
17.5
19.5
11
23.5
23
Vertical Jump Height
(in)
64
66
69
68
67
68
Correlation in SPSS

Analyze > Correlate > Bivariate …
A word about Tails…

Two-tailed test



Use if prior research or logical reasoning does not
clearly indicate a significant difference between
the mean values should be expected
Will use most of the time
One-tailed test

Use if the direction (+ or -) of the difference
between the means is well established before
data collection
Sample Correlation Output
De scri ptive Statistics
VJ
Height
Mean
17.667
67.00
St d. Deviat ion
5.4467
1.789
N
6
6
R value
Corre lations
VJ
VJ
Height
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
6
.431
.393
6
Height
.431
.393
6
1
6
Significance
Significance

The probability that:




a result is not likely to be due to chance alone
a result is correct
Expressed as a p value (probability value)
In research, significance is set before
collecting data
Levels of Confidence &
Probability of Error

In general, statistical significance is reported
at one of three levels:




If p=0.01, 99% confident the results are correct
and 1% incorrect
If p=0.05, 95% confident the results are correct
and 5% incorrect
If p=0.10, 90% confident the results are correct
and 10% incorrect
If p>0.10, don’t report at all, because not
statistically significant
Significance Example



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Suppose SPSS gives p = 0.02
At which level is this value significant?
To answer this question, compare p value to
each level of confidence
If p is less than a given level, try the next



P < 0.10
P < 0.05
P < 0.01
Significance example, con’t.
Report
as NS.
No
Is p < 0.10 ?
Y
Report
as
p<.10
No
Is p < 0.05 ?
Y
Report
as
p<.05

No
Is p < 0.01 ?
Yes
Report
as
p<.01
For p=0.02,

We say p is significant at p<0.05 or at the 95% LOC
Correlation Significance
Example


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R=0.75 but p=0.35
Obtained a moderate correlation, but we are
only 65% certain results are correct and due
to chance
P=0.35 is not statistically significant, so we
can conclude results not due to chance
Possible reasons


Sample is not representative of population
Data has been tampered with in some way
T-test
Use to compare one sample mean to the
population mean
-OR Use to compare two independent, unrelated
samples drawn from same population



Tells us if the two means are statistically
different
Like correlation, the T test does not
indicate causation
Types of T tests

Independent Samples



Run this test if just need to compare the means
between two groups
e.g. Obtained VO2max scores from Kin 260 Sec 1
and Sec 3. Want to compare the means between
the two sections
Paired Samples


Run this test if research design required a pre and
post test and same subjects were tested twice
e.g. All Kin 260 students took a VO2max test
before beginning a conditioning program, then took
another VO2max test 6 weeks later.
Ex – Independent Sample T Test


A biomechanics student gave a sit-and-reach test to 10 male
and 10 female undergrads.
The following measurements in cm were obtained:
Males
Females
19.1
20.4
17.2
25.0
20.1
26.9
18.2
27.1
16.5
28.3
16.9
22.2
21.2
23.8
19.7
24.8
15.9
25.4
16.0
19.0
T-Test Example con’t.



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Male mean = 18.1
Female mean = 24.3
Appears females are more flexible at the hip
than males
But is this difference statistically significant?
T-test: SPSS
Define variables in Variable View
1.
-
2.
3.
4.
5.
ONE BIG DIFFERENCE: Need to create a
“grouping” variable using Value Labels
Enter data in Data View
Analyze > Compare Means > Independent
Samples T test…
Add variables
Define Groups
T-test: SPSS con’t.
T test: SPSS
T-test: SPSS Output
•SPSS reports highly significant values as 0.00
- take this to be p<0.01
• So t = 5.573 and p<0.01
T test - Results

If p<0.10, get to say difference between the
means is statistically significant



report t value and level of confidence
But remember t value does not tell us why the
means are different
If p>0.10, report as NS (not significant)


One or both of these samples were not randomly
drawn, OR
Some factor has affected these samples, causing
them to be different from the original population
Ex – Paired T test
•A running coach gave a 1.5 mile running test to
her athletes before and after a 3 wk
cardiovascular training program
•Did the training program improve running time?
Pre (min)
Post (min)
9.5
9.1
12.2
12.0
12.8
12.6
10.2
10.2
10.8
10.9
9.5
9.4
Paired t test steps similar to
independent t test
Define variables in Variable View
1.


2.
3.
4.
Do not need to use Value Labels
Set up variables in same manner as
correlation
Enter data in Data View
Analyze > Compare Means > Paired
Samples T test…
Add variables
Correlation vs. T-test

When and how to use each?
Correlation
Does x data predict y
data?
Can y data be predicted
from x data?
Graph in Excel, analyze
data in SPSS.
T test
Compare the means
between the two groups.
Compare the pre and post
tests.
Analyze data in SPSS.
More Information


SPSS:
http://www.calstatela.edu/its/docs/pdf/SPSS1
4Part2.pdf
T-tests:
http://en.wikipedia.org/wiki/Student's_t-test