Describes problems of assessing change with short time-series data: unreliability of visual inference and fact that current statistical procedures cannot control Type I error because they underestimate positive autocorrelation. Shows how problems can be solved with new interrupted time-series analysis procedure (ITSACORR) that uses more accurate estimate of autocorrelation. (Author/NB)