ex3ab07_comments - Language of evaluation 1,2. (3.5 pts...

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Language of evaluation 1,2. (3.5 pts each) We wish to test the model that red cars have at least 1.5 times higher accident rates (per car per mile) than white cars . 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: Accident rates by color of car per 10,000 miles: white = 1%, blue = 0.6% tan = 0.7% green = 0.4%, red = 1.5%. A B C D E since rate of red = 1.5X that of white, is both consistent and supports (since they could have gone the other way) 2) Data: Accident rates by color of car per 10,000 miles: white = 1%, blue = 0.6% tan = 0.7% green = 0.4%, red = 2%. A B C D E same logic as in (1): red = 2X that of white, which is also consistent with and supports the model 3. (8 pts) 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) More people attend the Kerrville Folk Music Festival than attend the Rice Festival. two variables (festival and # attending) and the number attending differs; so = a correlation (B) Two thirds of UT students voted in student government elections; one third did not vote. only one variable here, number of students voting (gives same info as # not voting). Need another election for a second variable. (C) Global average yearly temperatures have been increasing over the last few decades two variables: temperature and time; not constant, so = correlation (D) More people buy products endorsed by Michael Jordan than products endorsed by O.J. Simpson two variables: celebrity and number buying products; number buying products differs between the celebrities, so = a correlation (E) The world’s population has doubled in the last 60 years. two variables: time and population. The two change together, so = a correlation (F) Customer sales at Austin Restaurant Supply have been flat (unchanged) over the last 7 years. two variables: sales and time. However, sales have not been changing, so a zero correlation. You could also
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argue that there is only one variable, if you consider that, since sales have not changed, that is not a variable. (G) Retail sales in the U.S. are higher in December than in any other month.
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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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ex3ab07_comments - Language of evaluation 1,2. (3.5 pts...

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