Linear Correlation and Regression
Data-Import Version
r2 = the coefficient of determination;T the slope of the regression line;T the Y intercept of the regression line;T the standard error of estimate;T the value of t associated with the calculated value of r, along with the corresponding one- and two-tailed probabilities;T the residual for each value of Y, calculated as residual = Y(intercept+[slope(X)])T the lower and upper limits of the .95 and .99 confidence intervals for the correlation coefficient (rho) that exists within the bivariate population from which the sample is drawn; andT the lower and upper limits of the .95 and .99 confidence intervals for the slope of the regression. |
The logic and computational details of correlation and regression are described in Chapter 3 of Concepts and Applications. |
| Data Entry | Data Report |
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| X | Y
| N | Mean | Variance | Std.Dev. | Std.Err. | | |||||||||||
| r | r2 | Slope | Y Intercept | Std. Err. of Estimate |
| t | df |
| P | one-tailed | | two-tailed | |
| Lower Limit | Upper Limit | ||||
| 0.95 | | 0.99 | |
| Lower Limit | Upper Limit | ||||
| 0.95 | | 0.99 | |
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