Geographers use remote-sensing data from satellite pictures to identify urban land cover as either grassland, commercial, or residential. In Geographical Analysis (Oct. 2006), researchers from Arizona State, Florida State, and Louisiana State Universities collaborated on a new method for analyzing remote-sensing data. A satellite photograph of an urban area was divided into 4 × 4-meter areas (called pixels). Of interest is a numerical measure of the distribution of the sizes of gaps, or holes, in the pixel, a property called lacunarity. The mean and standard deviation of the lacunarity measurements for a sample of 100 pixels randomly selected from a specific urban area are 225 and 20, respectively. It is known that the mean lacunarity measurement for all grassland pixels is 220. Do the data suggest that the area sampled is grassland? Test at a = .01.