Chapter 13: Problem 47
Explain the difference between \(r\) and \(\rho\).
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Chapter 13: Problem 47
Explain the difference between \(r\) and \(\rho\).
These are the key concepts you need to understand to accurately answer the question.
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The data of Exercise 13.25 milk temperature and \(y=\) milk \(\mathrm{pH},\) yield $$ \begin{array}{lrlr} n=16 & \bar{x} & =42.375 & S_{x x} & =7325.75 \\ b & =-.00730608 & a=6.843345 & s_{e}=.0356 \end{array} $$ a. Obtain a \(95 \%\) confidence interval for \(\alpha+\beta(40)\), the mean milk \(\mathrm{pH}\) when the milk temperature is \(40^{\circ} \mathrm{C}\) b. Calculate a \(99 \%\) confidence interval for the mean milk \(\mathrm{pH}\) when the milk temperature is \(35^{\circ} \mathrm{C}\). c. Would you recommend using the data to calculate a \(95 \%\) confidence interval for the mean \(\mathrm{pH}\) when the temperature is \(90^{\circ} \mathrm{C}\) ? Why or why not?
A subset of data read from a graph that appeared in the paper "Decreased Brain Volume in Adults with Childhood Lead Exposure" (Public Library of Science Medicine [May 27.2008\(]\) : ell2) was used to produce the following Minitab output, where \(x=\) mean childhood blood lead level \((\mu \mathrm{g} / \mathrm{dL})\) and \(y=\) brain volume change a. What is the equation of the estimated regression line? \(\quad \hat{y}=-0.001790-0.0021007 x\) b. For this dataset, \(n=100, \bar{x}=11.5, s_{e}=0.032,\) and \(S_{x x}=1764\). Estimate the mean brain volume change for people with a childhood blood lead level of \(20 \mu \mathrm{g} / \mathrm{dL}\), using a \(90 \%\) confidence interval. c. Construct a \(90 \%\) prediction interval for brain volume change for a person with a childhood blood lead level of \(20 \mu \mathrm{g} / \mathrm{dL}\) d. Explain the difference in interpretation of the intervals computed in Parts (b) and (c).
Exercise 13.10 presented \(y=\) hardness of molded plastic and \(x=\) time elapsed since the molding was completed. Summary quantities included $$ n=15 \quad b=2.50 \quad \text { SSResid }=1235.470 $$ \(\sum(x-\vec{x})^{2}=4024.20\) a. Calculate the estimated standard deviation of the statistic \(b\) b. Obtain a \(95 \%\) confidence interval for \(\beta,\) the slope of the population regression line. c. Does the interval in Part (b) suggest that \(\beta\) has been precisely estimated? Explain.
In a study of bacterial concentration in surface and subsurface water ("Pb and Bacteria in a Surface Microlayer" journal of Marine Research [1982]: \(1200-\) 1206 ), the accompanying data were obtained. Concentration \(\left(\times 10^{6} / \mathrm{mL}\right)\) \(\begin{array}{llllll}\text { Surface } & 48.6 & 24.3 & 15.9 & 8.29 & 5.75 \\\ \text { Subsurface } & 5.46 & 6.89 & 3.38 & 3.72 & 3.12 \\ \text { Surface } & 10.8 & 4.71 & 8.26 & 9.41 & \\ \text { Subsurface } & 3.39 & 4.17 & 4.06 & 5.16 & \end{array}\) Summary quantities are \(\sum x=136.02 \sum y=39.35\) \(\sum x^{2}=3602.65 \sum y^{2}=184.27 \quad \sum x y=673.65\) Using a significance level of \(.05,\) determine whether the data support the hypothesis of a linear relationship between surface and subsurface concentration.
The accompanying summary quantities for \(x=\) particulate pollution \(\left(\mu \mathrm{g} / \mathrm{m}^{3}\right)\) and \(y=\) luminance \((.01 \mathrm{~cd} /\) \(\mathrm{m}^{2}\) ) were calculated from a representative sample of data that appeared in the article "Luminance and Polarization of the Sky Light at Seville (Spain) Measured in White Light" (Atmospheric Environment [1988]\(: 595-599) .\) $$ \begin{aligned} n &=15 & \sum x=860 & \sum y=348 \\ \sum x^{2} &=56,700 & \sum y^{2}=8954 & \sum x y=22,265 \end{aligned} $$ a. Test to see whether there is a positive correlation between particulate pollution and luminance in the population from which the data were selected. b. What proportion of observed variation in luminance can be attributed to the approximate linear relationship between luminance and particulate pollution?
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