Linear Correlation and Regression
Direct-Entry Version
For a sample of N bivariate values of X and Y, this page will calculate:T
  • r = the Pearson product-moment correlation coefficient;T
  • 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)])     and: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.

The logic and computational details of correlation and regression
are described in Chapter 3 of Concepts and Applications.



Data EntryT
Data Cells
Pairs
X
Y
Residuals

Data SummaryT
iX =

  iX2i =

iY =

  iY2i =

iXY =

X Y


Mean 


Variance 


Std.Dev. 


Std.Err. 


r
r2
Slope
Y
Intercept

Std. Err. of
Estimate






t
df
  P   one-tailed
two-tailed

0.95 and 0.99 Confidence Intervals of rhoT
Lower Limit Upper Limit
0.95
0.99



Home Click this link only if you did not arrive here via the VassarStats main page.


©Richard Lowry 2001-
All rights reserved.