measured every second, and the TIE observation interval is in- creasing by one second at every observation. Although the curve will be the same, there is an offset, because the TIE value was defined to be at 0 at the start of the test. Figure 5-16 shows this example case, where the plotted TIE graph looks the same as a plot of time error with a constant offset because the TIE value starts at 0. The list that follows explains this fig- ure in more detail. Time error (in ns) Time error (TE) measures the time difference between two clocks (in seconds) Time interval error (in ns) Time interval error (TIE) measures "change" of time error (dTE) TIE starts at "0" (in seconds) Figure 5-16 Graph Showing TE and TIE Measurements and Plots As shown in Figure 5-16, the TE is +10 ns at the start of a measurement (TE0), at t = 0. There- fore, TE is +10 ns (measured), and the TIE is zero (by convention). Assume that the observation interval is 1 second. After the first observation interval, from Fig- ure 5-16, TE1 is 15 ns. The TIE calculated for this interval will be (TE1 - TE0) = 5 ns. After the second observation interval, assume TE2 is 0 ns. The TIE calculated now will be ( TE2 - TE0) = -10 ns. Note that this calculation is for the second observation interval and the interval for calculations really became 2 seconds. The observation interval keeps increasing until the end of the entire measurement test. There are other clock metrics (discussed later in this chapter), such as MTIE and TDEV, that are calculated and derived from the TIE measurements. TIE, which is primarily a measurement of phase accuracy, is the fundamental measurement of the clock metrics. Some conclusions that you can draw based on plotted TIE on a graph are as follows: An ever-increasing trend in the TIE graph suggests that the measured clock has a frequency off- set (compared to the reference clock). You can infer this because the frequency offset will be seen in each time error value and hence will get reflected in TIE calculations. If TIE graph shows a l