PSYCH 2300

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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

Card Set Information

PSYCH 2300
2013-07-02 16:30:10
Chapter 15

Correlation and Regression
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