A modified paired t-test for the analysis of plant trials with data autocorrelated in time

Sequential plant performance data, such as daily metal recovery, are shown to follow a first order autoregressive time series model. This has been use d to modify the standard formula for the paired t-test in evaluating on-off trials of alternative operating conditions, such as a new flotation reagen t or circuit configuration. The modified test is more powerful than the sta ndard test, requiring less trials to reach a decision at a given level of c onfidence. The power increases with the value of the AR(1) autocorrelation coefficient. The paper gives formulae for the modified test and for calculating the numb er of data pairs required to detect a given difference at a particular conf idence level. An example of the use of the new test is given. (C) 1999 Else vier Science Ltd. All rights reserved.