Title: Effect of Violations of Normality
1Effect of Violations of Normality
On the Correlation Coefficient t-Test
2Is the t-test for correlation coefficients robust
to violations of its assumptions?
3Overview
- Review t-test of the Correlation Coefficient
- Violations
- Bivariate Normal Assumption
- Independence Assumption
4Review Violation of Normality
Violation of Independence
t2 r2 / ((1-r2)/df)
- Bivariate normal assumption
- Both variables come from normal distributions
- OR
- One variable is from a normal distribution and
the variables are independent - Independence assumption
- Value of one variable is not influenced by the
other
5Review Violation of Normality
Violation of Independence
Method
- Run 10,000 samples
- Very Non-normal distributions
- Range of sample sizes
- Determine the proportion of samples that were
significant at the .05 and .01 level
6Review Violation of Normality
Violation of Independence
Distributions
Exponential Distribution
7Review Violation of Normality
Violation of Independence
Distributions
Uniform Distribution
8Review Violation of Normality
Violation of Independence
Distributions
Cauchy Distribution
9Review Violation of Normality
Violation of Independence
Results
10Review Violation of Normality
Violation of Independence
Results
11Review Violation of Normality
Violation of Independence
Method
- Run 10,000 samples
- Range of sample sizes
- Zero correlations with dependency
- Determine the proportion of samples that were
significant at the .05 and .01 level
12Review Violation of Normality
Violation of Independence
Method
- Zero-Correlations with dependency
- 1) Second variable is the square of the First
Variable - 2) Mixed Bivariate Normal Distributions
- - Population is aggregate of smaller
subpopulations
13Review Violation of Normality Violation
of Independence
Mixed Bivariate Normal Distributions
P.5 ?1.3
P.5 ?2 -.3
? 0
14Review Violation of Normality
Violation of Independence
Results
15Conclusion
Is the t-test for correlation coefficients robust
to violations of normality?
- Violations of Normality
- Robust at .05
- At .01, only sensitive to extreme departures from
normality
16Conclusion
Is the t-test for correlation coefficients robust
to violations of independence?
- But
- Non independent variables are not likely to have
a correlation of zero - t-Test could be considered a test of the
hypothesis of independence