Source: page 102, Applied Linear Regression, 2nd Ed., by Weisberg.
Originally from the 1977 Canadian Wildlife Service West Hudson Bay
snow goose survey, unpublished report by Cook and Jacobsen (1978).
"Geese" <-
structure(list(photo = c(56, 38, 25, 48, 38, 22, 22, 42, 34,
14, 30, 9, 18, 25, 62, 26, 88, 56, 11, 66, 42, 30, 90, 119, 165,
152, 205, 409, 342, 200, 73, 123, 150, 70, 90, 110, 95, 57, 43,
55, 325, 114, 83, 91, 56), obs1 = c(50, 25, 30, 35, 25, 20, 12,
34, 20, 10, 25, 10, 15, 20, 40, 30, 75, 35, 9, 55, 30, 25, 40,
75, 100, 150, 120, 250, 500, 200, 50, 75, 150, 50, 60, 75, 150,
40, 25, 100, 200, 60, 40, 35, 20), obs2 = c(40, 30, 40, 45, 30,
20, 20, 35, 30, 12, 30, 10, 18, 30, 50, 20, 120, 60, 10, 80,
35, 30, 120, 200, 200, 150, 200, 300, 500, 300, 40, 80, 120,
60, 100, 120, 150, 40, 35, 110, 400, 120, 40, 60, 40)), .Names = c("photo",
"obs1", "obs2"), row.names = c("1", "2", "3", "4", "5", "6",
"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28",
"29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39",
"40", "41", "42", "43", "44", "45"), class = "data.frame")