# PSYCH 2300

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 Author: xx.chelsii ID: 225636 Filename: PSYCH 2300 Updated: 2013-07-02 12:30:10 Tags: Chapter 15 Folders: Description: Correlation and Regression Show Answers:

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1. Correlation
Statistical technique that is used to measure and describe a relationship between two variables
2. Positive Correlation
The two variables tend to change in the same direction.

As the value of X increases, the Y also increases. Vice Versa
3. Negative Correlation
• Two variables go in opposite directions.
• As X increases, Y decreases - an inverse relationship
4. Perfect Correlation
Identified by a correlation of 1.00 and indicates a perfectly consistent relationship
5. Pearson Correlation
Measures the degree to and direction of the linear relationship between two variables
6. Sum of Products or SP
Measure the amount of co-variability between TWO variables

7. Restricted Range
A correlation that is computed from scores that do not represent the full range of possible values, should be cautious when interpreting correlation.
8. Coefficient of determination =
• Measures the proportion of variability in one variable that can be determined from the relationship with the other variable.
• A correlation of r=0.80 (or -0.80), means that  =0.64 (or 64%) of the variability in the Y scores can be predicted from the relationship with X
9. Linear Relationship
• A linear relationship between two variables can be expressed by the equation:
• Where a and b are fixed constants
10. Linear Equation
11. Slope
Slope determines how much the Y variable changes when X is increased by 1 point
12. Y-Intercept
• Determines the value of Y when X=0
• a value
13. Regression
Statistical technique for finding the best fitting straight line for a set of data
14. Regression Line
The resulting straight line
15. Least-squared-error
• The best fitting line has the smallest total squared error
16. Regression Equation for Y
17. Standard Error of Estimate
Gives a measure of the standard distance between a regression line and the actual data points
18. Predicted Variability (SSregression)
A statistical technique used to measure the amount of variance in a data set that is not explained by the regression model
19. Unpredicted Variability (SSresidual)
residual of an observed value is the difference between the observed value and theestimated function value

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