Practice Exam 3_summer

# Practice Exam 3_summer - Practice Exam 3-Summer A 2007 1....

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Practice Exam 3-Summer A 2007 1. If Ŷ=2+3X 1 +5X 2 -8X 3 , then controlling for X 2 and X 3 , the predicted mean change in Y when X 1 is increased from 10 to 20 is which of the following? a. 3 b. 30 c. 0 .3 d. Cannot be given-depends on specific values of X 2 and X 3 . 2. For a linear model with two independent variables X 1 and X 2 , which of the following must be incorrect? a. R 2 = 75% b. The sum of squared errors for the given model exceeds the sum of squared errors for the model alone with X 1 alone as the independent variable. c. The sum of squared errors for the model alone with X 1 alone as the independent variable exceeds the sum of squared errors for the given model. d. R 2 for the model alone with X 1 alone as the independent variable is less than the R 2 for the given model. Problems 3-7: A basket ball player made only 36.2% of her throws last season. She develops a new shot to improve her free-throw accuracy. In the first eight games of this season the player makes 22 free throws in 42 attempts. Let p be the probability of making each throw she shoots during this season. 3. What is the sample estimate of p? a. 0.5238 b. 0.362 c. 0.125 d. 0.4762 4. Suppose the player wants to test whether her new shot has improved the probability of making a free-throw. What appropriate hypotheses would you suggest? a. H 0 : p 36.2, H 1 : p 36.2 b. H 0 : p 0.362, H 1 : p 0.362 c. H 0 : p 0.362, H 1 : p 0.362 d. H 0 : p 36.2, H 1 : p 36.2 e. None of the above. 5. What is the value of the test statistic for the appropriate test? a. 2.18 b. 2.14 c. 2.25 d. 2.29 1

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6. What is the 90% confidence interval for p? (Use Wilson’s estimate of p) a. (0.397, 0.651) b. (0.401,0.643) c. (0.377,0.666) d. (0.373,0.675) 7. Suppose you want to estimate the probability of making a free-throw within a margin of error of ± 0.05 at 90% confidence level. What should be the size of your sample, or in other words, how many free-throws should you observe? (you can take the last season’s success rate as the value of p) a. 100 b. 351 c. 42 d. 246 Problems 8-11 . In rock blasting, an engineer suggests predicting the peak particle velocity (PPV) (y) from the scaled distance (x), which is equal to the distance from the blast divided by the square root of the charge. Following is the MINITAB output (incomplete) for fitting a simple linear regression of y on x: y=β 0 + β 1 x+ε, ε~N(0,σ 2 ) independently. Regression Analysis: PPV(mm/s) versus Sc. Distance(m/kg^0.5) Predictor Coef SE Coef T P Constant 12.490 3.440 3.63 0.003 Sc. Distance(m/kg^0.5) -0.3375 0.1335 -2.53 0.025 S = 6.11645 R-Sq = 33.0% R-Sq(adj) = 27.8% Analysis of Variance Source DF SS MS F P Regression 1 239.02 ? ? 0.025 Residual Error 13 ? ? Total
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## This note was uploaded on 08/05/2011 for the course STA 3032 taught by Professor Kyung during the Summer '08 term at University of Florida.

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Practice Exam 3_summer - Practice Exam 3-Summer A 2007 1....

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