Relative Efficiency of Count of Sign Changes for Assessing Residual Autoregression in Least Squares Regression

From a constructed example of 100 random samples of size 40, in conjunction with the author's ACV method for comparing the relative efficiency of different tests of significance, it is found that a simple count of sign changes is nearly as efficient as the familiar Durbin-Watson test of autoregression of residuals. Individual decisions based on this test are closely similar to those from the number of runs test. On another actual body of data the three tests seem to be about equally efficient. A table is supplied giving cumulative binomial probabilities for assessing significance for the sign changes test.