# Stats I Final Pitt 3

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1. What is correlation?

correlation
measures the relationship between two variables

there are more than one type of correlation (depending on level of measurement)
2. Pearson product moment correlation

correlation
between interval/ratio variables

most widely used measure of correlation

has the most assumptions
3. Speraman rank correlation

correlation
between ordinal variables
4. Phi coefficient

correlation
between dichotomous variables
5. point-biserial correlation

correlation
between a dichotomous & interval/ration variables

ex: right or wrong of an exam item and total score
6. biserial correlation

correlation
between a dichotomous (w/ underlying continuum) & interval/ratio variables

ex:anxiety (low, high) & depression
7. polyserial correlation

correlation
between a polytomous (3 or more levels) (w/ underlying continuum) & interval/ratio variables

ex: anxiety (low, medium, high) & depression
8. tetrachoric correlation

correlation
betwee dichotomous variables (w/ underlying continuum) and depression

ex: anxiety (low, high) & depression (low, high)
9. polychoric correlation

correlation
between polytomous variable (w/ underlying continuum)
10. Pearson Product Moment Correlation Assumptions

correlation
No Outliers

Linearity

Normal Distribution
11. Pearson Assumptions: No Outliers

correlation
no extreme scores

• two types:
• -univariate
• -multivariate
12. Pearson Assumption: No Outliers - Univariate

correlation
an extreme score that is far away from the distribution of a variable

-only one variable
13. Pearson Assumption: No Outliers - Multivariate

correlation
an extreme score that is far away from the joint distribution of variables

it is possible for a case to be a multivariate outlier without bieng a univaritate outlier
14. Pearson Assumption: Linearity

correlation
variables should NOT show any non-linear pattern
15. Pearson Assumption: Normal Distribution

correlation
distribution of a variable should be univariate normal

distribution of variables should be multivariate normal
16. Range of Correlation

correlation
• all correlation range from -1 to +1
• a measure of correlation is unitless (or standardized).

• r = -1 perfect negative relationship
• r = +1 perfect positive relationship
• r = 0 no relationship
17. Scatterplot

correlation
when the correlation is r= +1, the scatterplot appears in a straight line

as the correlation approaches 0, the variability of scores increases
18. Covariance

correlation
measures of relationship between two variables in raw units (unstandardized correlation)

possible range is -infinity to +infinity
19. Types of Research Questions

correlation
1. Is there a significant relationship between x and y?

2. Is there a significant difference in the relationship of x and y between group 1 and group 2?

3. What is the (1-alpha)%CI of the correlation?
20. Sampling Distribution Correlation

correlation
• in not normal except when r=0 due to restricted range of the correlation
• -bound between -1 & +1
21. One-sample t-test for correlation

correlation
For testing H0: p = 0, Greek letter rho - population correltaion

df = N - 2

affected not only by N but also by r. Depends on the # of subjects & relationship
22. When to us r-critical

correlation
when testing more than one correlation becomes tedious

easier to compute r-critical value as long as there are same N
23. Fisher's r-to-z transformation

when to use

correlation
For testing a H0: p = p0

For difference in a correlation between groups

For confidence interval of a correlation

Convert r to z-score
 Author: Anonymous ID: 187294 Card Set: Stats I Final Pitt 3 Updated: 2012-12-05 15:55:31 Tags: Correlation Folders: Description: Stats I Finall Pitt part 3 Show Answers: