SPSS Part 2

Kin 260

Jackie Kiwata

Overview

Review Comparing Sets of Data

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

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 Review

Correlation: SPSS example Research question: Can a person’s height predict

their vertical jump height?

Height (in) Vertical Jump Height (in)

11.5 64

17.5 66

19.5 69

11 68

23.5 67

23 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

Descriptive Statistics

17.667 5.4467 6

67.00 1.789 6

VJ

Height

Mean Std. Deviation N

Correlations

1 .431

.393

6 6

.431 1

.393

6 6

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

VJ

Height

VJ Height

R value

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

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.

For p=0.02, We say p is significant at p<0.05 or at the 95% LOC

Is p < 0.10 ?

No

Report as NS.

Yes

Y

Is p < 0.05 ?

No

Report as p<.10

Y

Is p < 0.01 ?NoReport as p<.05

Report as p<.01

Correlation Significance Example

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.

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: SPSS1. Define variables in Variable View

- ONE BIG DIFFERENCE: Need to create a “grouping” variable using Value Labels

2. Enter data in Data View

3. Analyze > Compare Means > Independent Samples T test…

4. Add variables

5. 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

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

•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?

Paired t test steps similar to independent t test

1. Define variables in Variable View Do not need to use Value Labels Set up variables in same manner as

correlation

2. Enter data in Data View

3. Analyze > Compare Means > Paired Samples T test…

4. Add variables

Correlation vs. T-test

When and how to use each?

Correlation T test

Does x data predict y data?

Compare the means between the two groups.

Can y data be predicted from x data?

Compare the pre and post tests.

Graph in Excel, analyze data in SPSS.

Analyze data in SPSS.

More Information

SPSS: http://www.calstatela.edu/its/docs/pdf/SPSS14Part2.pdf

T-tests: http://en.wikipedia.org/wiki/Student's_t-test