Terminal abdominal cancer

1. J. Gould, in" rel="nofollow">in 1982, faced a harsh diagnosis of termin" rel="nofollow">inal abdomin" rel="nofollow">inal cancer. He researched and learned the median life-expectancy for a person given a like diagnosis, and in" rel="nofollow">initially was discouraged (as many cancer diagnosed patients are on receivin" rel="nofollow">ing their diagnoses).Though as an evolutionary biologist, another "hard reality" of statistics emerged that allowed him to craft and adopt a statistical strategy for dealin" rel="nofollow">ing with the reality of the median life-expectancy for similar diagnoses. What was the statistical strategy Gould adopted? (1 poin" rel="nofollow">int; a succin" rel="nofollow">inct phrase or sentence, please): 2a. (1/2 pt.) What can you glean as the shape of the distribution Gould found himself up again" rel="nofollow">inst on receivin" rel="nofollow">ing his diagnosis? (normal, symmetricaVskewed—left-hand, or right-hand). b) (1/2 pt) What details in" rel="nofollow">in Gould's description of the distribution allow you to know this shape? 3. (1 pt.) usin" rel="nofollow">ing Gould's example as a model, describe one of the promin" rel="nofollow">inent parameters (shape, spread, center) of a distribution you, a friend, or a family member has had to confront in" rel="nofollow">in their lifetimes; one, whose parameters you have learned by "comin" rel="nofollow">ing up again" rel="nofollow">inst" that distribution, much as Gould did.