– 17 – 7. Summary Amongst all the extragalactic classes of objects, AGNs are the primary sources able to produce significant changes in their mid-IR luminosity over a several year timescale. Thus, mid-IR variability may be used as a new tool for selecting AGNs, especially if combined with other methods. However, in our relatively shallow few-epoch survey, only ∼ 15% of AGNs are sufficiently variable to be detected; therefore, variability-selected samples of AGNs We study the mid-IR variability of objects based on the significance level of their joint variability ( σ$_{12}$ ) in both the [3.6] and [4.5] channels focusing on the sources that also show a high correlation ( r > 0 . 8) between the two channels. Our standard selection criteria with σ$_{12}$ > 2 identify ∼ 5100 objects as variables, which constitute 1.1% of all detected sources in the field. We find that the majority (76%) of the mid-IR variable sources in the NDWFS Bo¨ otes field are AGNs, where we define AGNs to be objects that satisfy any of the following criteria: (1) lie inside the modified AGN wedge, (2) are X-ray, 24 µ m or radio AGN candidates, (3) have z > 1, or (4) have an AGN spectroscopic template in any region. In this paper, we performed DIA photometry on the four epochs of SDWFS data. The common area of the Spitzer mosaics covers 8.1 deg 2 of the NDWFS Bo¨ otes field, and contains 474 , 179 mostly extragalactic objects. We concentrate on the deeper 3.6 and 4.5 µ m channels, and provide variability catalogs and light curves. These variability data are cross-correlated with the AGES redshift survey, X-ray and radio data, and 24 µ m AGN candidates from the same area of the sky to study the variability of various classes of objects. In general, the statistics of these simulated light curves agree with observations, indicat- ing that our estimates of the structure function are correct. However, they also show that we are “pushing the envelope” of variability, because for most AGNs the variability amplitudes are merging into the measurement uncertainties, as can be seen in Figure 2. (see Rybicki & Press 1992). If we assume the variability in both bands is identical but the noise is independent, then we can compute the fraction of such AGNs we would select as a function of the noise σ using Monte Carlo simulations. Figure 10 shows the approximate completeness as a function of magnitude for sources with r > 0 . 8 and either σ$_{12}$ > 2 or 4. We use the observed structure function and the normalized measurement uncertainties to track the median values for [3.6] in Figure 2. For simplicity, the [4.5] band is treated as being identical to the [3.6] band. As might be expected from the structure of Figure 2, the completeness is high when the measurement errors are small compared to the amplitude of the structure function and then drops rapidly for fainter sources.