exam3ab05 - Name (required) _ Language of evaluation 1-4)...

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Name (required) ___________________________ Language of evaluation 1-4) (2 pts each) We wish to test the model that players or teams with red sports uniforms have higher winning rates than players/teams wearing other colors of uniforms . For the following possible data, which consequences (A-D) apply? Note that this question is not about causation versus correlation, only about data and a model that happens to describe a correlation. Answer each question independently of the others. At least one answer, but possibly more (MTF). Ignore the possibility of sampling error. A) The data are inconsistent with the model B) The data are consistent with the model C) The data support the model D) The data are irrelevant to the model E) None 1) Data: Winning rates by color in 100 olympic contests: white = 13%, blue = 6% gold = 7% green = 4%, red = 8%, all others less than 3% each A B C D E 2) Data: Winning rates by color in 100 high school football championships: white = 5%, blue = 6% gold = 7% green = 4%, red = 9%, all others less than 3% each A B C D E 3) Data: 18% of basketball teams wear red; 15% of football teams wear red. A B C D E 4) Data: Winning rates of blue uniforms are 51% A B C D E 5) ( 7 pts ) The following points pertain to the book and lecture on evaluation. Which statements are true? MTF (A) Classifying data as irrelevant to a model means that the data were not gathered according to the Ideal Data template. (B) To “accept” a model means that it cannot be refuted in further tests. (C) The criteria for acceptance of a model are rigid in science and society, and there is little legitimate room for disagreement as to whether a model should be accepted or not. (D) A company wishing to obtain FDA approval to market a new drug must first show it is safe. This procedure thus uses the null model that the drug is harmful until proven safe. In contrast, for marketing an herbal remedy, there is no null model. (E) In science and in many aspects of society, our willingness to reject a null model increases as evidence accumulates against that model. For example, in class, our acceptance of the safety of a vaccine (against the null model that the vaccine was not safe) increased as the sample of successful trials increased. (F) A null model is part of every properly designed study. If the study does not have a null model, then it is not properly designed. 1 Bio301D Exam 3 2005
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Name ____________________ Correlations 6. (5pts) Which of the following statements describe a (non-zero) correlation? Do not choose any option that describes a zero correlation or for which a correlation is undefined. If insufficient information is given to determine whether a correlation exists, treat it as if there is no correlation. MTF (A) Memory loss increases with age. (B) As X increases, Y decreases
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This note was uploaded on 12/20/2010 for the course BIO 301D taught by Professor Bull during the Spring '08 term at University of Texas at Austin.

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exam3ab05 - Name (required) _ Language of evaluation 1-4)...

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