An Introduction to Statistical Methods and Data Analysis
An Introduction to Statistical Methods and Data Analysis
7th Edition
ISBN: 9781305269477
Author: R. Lyman Ott, Micheal T. Longnecker
Publisher: Cengage Learning
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Is a baseball players' slugging percentage correlated to their strikeout percentage? A random sample of n=6n=6professional baseball players gave the following data (Source: baseball-reference.com) Slugging 0.396 0.42 0.323 0.078 0.473 0.467 Strikeouts 27 14.3 30.8 47.1 17.8 36.7 Find the least squares line if we consider slugging percengtage as the explanatory variable and strikeout percentage as the response variable. (Round the y-intercept and slope to 2 decimal places.)y^ =   For a unit increase in slugging percentage, how much of a  decrease Correct in strikeout percentage is predicted? (Round your answer to 2 decimal places.) What percentage of the variation in strikeout percentage (yy) can be explained by slugging percentage (xx) and the least squares line? (Round to the nearest percent.) p-value    (Round to four decimal places)
When using the least-squares line for prediction, are results more reliable for extrapolation or interpolation? a.   Interpolation, because we are predicting from data outside the range used to create the least-squares line. b.   Extrapolation, because we are predicting from data outside the range used to create the least-squares line. c.   Extrapolation, because we are predicting from data in the range used to create the least-squares line. d.   Interpolation, because we are predicting from data in the range used to create the least-squares line.
The following table shows the assessed values and the selling prices of eight houses, constituting a random sam-ple of all the houses sold recently in a metropolitan area: Assessed value Selling price(thousands) (thousands)(of dollars) (of dollars)170.3 214.4202.0 269.3162.5 206.2174.8 225.0157.9 199.8181.6 232.1210.4 274.2188.0 243.5 (a) Fit a least squares line that will enable us to predictthe selling price of a house in that metropolitan area interms of its assessed value. (b) Test the null hypothesis β = 1.30 against the alterna-tive hypothesis β > 1.30 at the 0.05 level of significance.
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