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Unformatted text preview: Stat 119 Quiz SB Name: E
Red id: 1. (2 points) Piestudy scores versus poststudy scores for a ciass of 120 college freshman
English students were considered. The residual plot for the least squares regression time showed no pattern. The least squares regression line was x 0.2 + 0.9x with a
correlation coefficient r = 0.76. What percent of the variation of poststudy scores can be
entrained by the variation in piestudy scores? B. 23:33: %’h 2:. Seat as C. 76.0% D. 52.0% B. We cannot determine the answer using the information given.
Answer: Ex.) (2 points) The National Opinion Research Center at the University of Chicago conducted
a survey where they obtained data involving the number of hours of watching television
in a typical day and the age of 1913 randomly sampled participants. The resnlting
regression equation and correlation coefficient were; 5; = 2.19+0.0l73x with r=0.632
X where hours of watching television was the response variable and age was the expianatory variable. The correct way to interpret this slope is; . For every 1 year increase in age, there is a 2.i9 hour increase in television watching. For every 1 year increase in age, hours of watching television increase by 0.0173. . For every 1 hour increase in television watching, age increases by 0.0173. D. For every i year increase in age, hours of watching television increase by 0.632 E. For every 1 hour increase in television watching, age increases by 239. Answer: (2 points) Which of the following is true about the coefficient of determination? . The tower it is the better the predictive power.
. It is equal to the square root of the correlation coefﬁcient. Its values range from ml to l. 3 is the fraction (percent) of the variation accounted for by the linear relationship. 4. (2 points) A residual plot with had predictive power could have any of the following
characteristics except which one of the following? A. Large Residuals I mall Residuals C. Curvature D. Fanning Answer: Use the foliowing information to answer probiems 59
A geologist is studying the relationship between the weight of a tiger and the ti ger’s maximum speed. A sample of i5 tigers, with weights ranging from 145 to 300 kg, was selected. The tiger’s
weight and maximum speed (miles per hour) were recorded. The foltowing regression equation. was obtained: Maximum speed = 96.5761 w 03614 (weight) R—Squared = 78.9% 5. (3 points) Identify and interpret the slope of the liner
Slope: "’ t Interpretation: 6. (3 points) Calcuiate the correlation coefficient and use it to interpret the relationship
between weight and maxrmum speed: g s g g Correlation coefficientzwgg
Interpretation: 3 ha i: at; V4” jag“ {at W k; 7. (3 points) Suppose it is known that a 265 kg tiger has a maximum speed of 49 miies p6! hour. What is the residual for this model value? § : q w ‘ £§ g g £ x 5 73 . $9 5” g
A Rotated e. \i m» y
Answer: “9” £4" g; gmLf‘ 8. (1 point) What is the predicted maximum speed for a (300 kg tiger?
A. We can predict the maximum speed of the tiger is {12639 mph.
B, It is not reasonabie to make a prediction in this case: the relationship between weight and speed could not be linear It is not reasonable to make a prediction in this situation: 609 kg is not in the data range.
D. There must be a mistake in the regression equation: it is not possible to have a neative answer.
Answer: C 9. (2 points) The zoologist also recorded each ti ger’s age, to see whether there is a
correlation between the tiger’s age and speed. The percent of variabiiity in speed that is
explained by the tiger’s age is 81.3%. Which is the better predictor of tiger’s speed: weight or age? Expiain your choice. in age is What ii ...
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This note was uploaded on 05/04/2008 for the course STAT 119 taught by Professor Helen during the Spring '07 term at San Diego State.
 Spring '07
 Helen
 Statistics

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