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Unformatted text preview: Stat 119 Quiz 3A Name:
Red id: 1. (2 points) Pre—stucly scores versus post—study scores for a class of 120 college freshman
English students were considered The residual plot for the least squares regression line showed no pattern. The least squares regression line was $2 = 0.2 + 0.936 with a
correlation coefficient r = 0.76. What percent of the variation of post—study scores can be
explained by the variation in ore—study scores?
A. 76.0% L :31"
. 520% ”‘3’é if $W“ . ﬂ
57.8% I. 87.2% We cannot determine the answer using the information given.
Answer: 2. (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 atypical day and the age of 1913 randomiy sampled participants. The resulting
regression equation and correlation coefficient were; )3 m 2.19 + 0.01'73x with r x 0.632
‘X where hours of watching teievrsion was the response variabie and age was the explanatory variable. The correct way to interpret this slope is;
A. For every 1 year increase in age, there is a 2.19 hour increase in television watching. For every 1 hour increase in television watching, age increases by 0.0173. . For every 1 year increase in age, hours of watching television increase by 0.0173.
I For every '1 year increase in age, hours of watching television increase by 0.632 E. For every i hour increase in television watching, age increases by 2.19. Answer: "2 (2 points) Which of the following is true about the coefﬁcient of determination? Its values range from d to l.
 it is the fraction (percent) of the variation accounted for by the linear reiationship. 3. A. C. The lower it is the better the preciictive power. D. It is e nal to the square root of the correlation coefficient. Answer 4. (2 points) A residual plot with bad predictive power couici have any of the foliowing
characteristics except which one of the following? Small Residuals B.Large Residuals C. Curvature D. Fanning Answer: Use the following information to answer problems 59 A zoo'iogist is studying the relationship between the weight of a tiger and the tiger’s maximum
speed. A sample of £5 tigers, with weights ranging from 145 to 300 kg, was selected. The tiger’s
weight and rnaxitnum speed (roiies per hour) were recorded. The following regression equation was obtained:
Maximum speed m 96.576} — 0.1614 (weight) RSquared m 79.4% 5. (3 points) Identify and interpret the slope of the line. Slope: m “ l‘%% g interpretation: 6. (3 points) Calcalate the correlation coefficient and use it to interpret the relationship
between weight and maximum speed. .3 w 3% l g may Correlation coefficient: WQ’ %% l i Interpretation: 7. (3 points) Suppose it is known that a 255 kg tiger gas a maximum speed of 56 rhiies per
hour. What is the residual for this model vaine? w W§
Astana» as» two :2. 59 LHg‘ii
idhdlgy ”Q
Answer: “586% :géwsgeﬂl%l :3 °S§gﬁ 8. (1 point) What is the predicted maximum speed for a 600 kg tiger? A. We can predict the maximum speed of the tiger is {3.2639 mph. B. it is not reasonable to make a prediction in this case: the relationship between weight and speed could not be linear
C. There must be a mistake in the regression equation: it is not possible to have a
negative answer.
flt is not reasonable to make a prediction in this situation: 600 kg is not in the data
" range. Answer: 9. (2 points) The zoologist aiso recorded each tiger’s age, to see whether there is a
correlation between the tiger’s age and speed, The percent of variability in speed that is
explained by the tiger’s age is 61.3%. Which is the better predictor of tiger’s speed: weight or age? Explain your choice. ...
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 Spring '07
 Helen
 Statistics

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