ex4_fa06 - STA 6126 Fall 2006 Exam 4 Print Name _ UFID _ I...

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STA 6126 – Fall 2006 – Exam 4 Print Name ____________________ UFID _________________ I have not cheated on this exam. ________________ The slope of the least squares prediction equation and the Pearson correlation coefficient are similar in the sense that (Circle any that are True): They do not depend on the units of measurement They both must fall between -1 and +1 They both have the same sign They both have the same t staistic value for testing H 0 : Independence One can interpret r = 0.40 as (Circle any that are True): A 16% reduction in (total squared) error occurs when using X to predict Y as opposed to using Y to predict Y A 40% reduction in (total squared) error occurs when using X to predict Y as opposed to using Y to predict Y 16% of the time Y Y = ^ Y changes on average, by an estimated 0.40 units, for a one-unit increase in X When X is used to predict Y , the “typical” residual is 0.40. You find the following partial ANOVA table in the grad student computer lab in your department. Unfortunately, someone spilled coffee on it, and some values are unreadable. Complete the table from a simple linear regression model. Source                df        sum Squares     mean square       F Regression           1
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This note was uploaded on 01/15/2012 for the course STA 6126 taught by Professor Yesilcay during the Spring '08 term at University of Florida.

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ex4_fa06 - STA 6126 Fall 2006 Exam 4 Print Name _ UFID _ I...

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