PSYCH 2300
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Correlation
Statistical technique that is used to measure and describe a relationship between two variables

Positive Correlation
The two variables tend to change in the same direction.
As the value of X increases, the Y also increases. Vice Versa

Negative Correlation
 Two variables go in opposite directions.
 As X increases, Y decreases  an inverse relationship

Perfect Correlation
Identified by a correlation of 1.00 and indicates a perfectly consistent relationship

Pearson Correlation
Measures the degree to and direction of the linear relationship between two variables

Sum of Products or SP
Measure the amount of covariability between TWO variables

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.

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

Linear Relationship
 A linear relationship between two variables can be expressed by the equation:
 Where a and b are fixed constants


Slope
Slope determines how much the Y variable changes when X is increased by 1 point

YIntercept
 Determines the value of Y when X=0
 a value

Regression
Statistical technique for finding the best fitting straight line for a set of data

Regression Line
The resulting straight line

Leastsquarederror
 The best fitting line has the smallest total squared error

Regression Equation for Y

Standard Error of Estimate
Gives a measure of the standard distance between a regression line and the actual data points

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

Unpredicted Variability (SSresidual)
residual of an observed value is the difference between the observed value and theestimated function value