/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 16 A sample of automobiles traversi... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

A sample of automobiles traversing a certain stretch of highway is selected. Each one travels at roughly a constant rate of speed, although speed does vary from auto to auto. Let \(x=\) speed and \(y=\) time needed to traverse this segment of highway. Would the sample correlation coefficient be closest to \(.9, .3,-.3\), or \(-.9 ?\) Explain.

Short Answer

Expert verified
The sample correlation coefficient would be closest to -0.9. This is due to the strong negative correlation between the speed of an automobile and the time it takes to traverse a specific segment of highway.

Step by step solution

01

Understand the Concept of Correlation Coefficient

The correlation coefficient measures the degree of linear relationship between two variables. It ranges from -1 to 1. A correlation coefficient of -1 indicates a perfect negative correlation, where an increase in one variable corresponds to a decrease in the other. In contrast, a correlation coefficient of 1 indicates a perfect positive correlation, where both variables increase or decrease together. A coefficient close to 0 indicates no linear correlation.
02

Apply the Concept to the Current Problem

In this case, the speed of automobiles (\(x\)) and the time needed to traverse a certain distance (\(y\)) have an inverse relationship. This means when the speed increases, the time needed to traverse that distance decreases. Therefore, the correlation is expected to be negative.
03

Choose the Correct Correlation Coefficient from the Provided Choices

Given the options of .9, .3, -.3, and -.9, the correlation coefficient that best fits the relationship in this situation is -0.9. This is because -0.9 signifies a very strong negative relationship, which is what you would expect for speed and travel time: as speed increases, travel time decreases substantially.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Is the following statement correct? Explain why or why not. A correlation coefficient of 0 implies that no relationship exists between the two variables under study.

The paper "Effects of Canine Parvovirus (CPV) on Gray Wolves in Minnesota" (Journal of Wildlife Management \([1995]: 565-570\) ) summarized a regression of \(y=\) percentage of pups in a capture on \(x=\) percentage of \(\mathrm{CPV}\) prevalence among adults and pups. The equation of the least-squares line, based on \(n=10\) observations, was \(\hat{y}=62.9476-0.54975 x\), with \(r^{2}=.57\) a. One observation was \((25,70)\). What is the corresponding residual? b. What is the value of the sample correlation coefficient? c. Suppose that \(\mathrm{SSTo}=2520.0\) (this value was not given in the paper). What is the value of \(s_{e} ?\)

A study was carried out to investigate the relationship between the hardness of molded plastic \((y\), in Brinell units) and the amount of time elapsed since termination of the molding process \((x\), in hours). Summary quantities include \(n=15\), SSResid \(=1235.470\), and SSTo = \(25,321.368\). Calculate and interpret the coefficient of determination.

The article "Examined Life: What Stanley H. Kaplan Taught Us About the SAT" (The New Yorker [December 17,2001\(]: 86-92\) ) included a summary of findings regarding the use of SAT I scores, SAT II scores, and high school grade point average (GPA) to predict first-year college GPA. The article states that "among these, SAT II scores are the best predictor, explaining 16 percent of the variance in first-year college grades. GPA was second at \(15.4\) percent, and SAT I was last at \(13.3\) percent." a. If the data from this study were used to fit a leastsquares line with \(y=\) first-year college GPA and \(x=\) high school GPA, what would the value of \(r^{2}\) have been? b. The article stated that SAT II was the best predictor of first-year college grades. Do you think that predictions based on a least-squares line with \(y=\) first-year college GPA and \(x=\) SAT II score would have been very accurate? Explain why or why not.

'The article "Reduction in Soluble Protein and Chlorophyll Contents in a Few Plants as Indicators of Automobile Exhaust Pollution" (International Journal of Environmental Studies [1983]: \(239-244\) ) reported the following data on \(x=\) distance from a highway (in meters) and \(y=\) lead content of soil at that distance (in parts per million): a. Use a statistical computer package to construct scatterplots of \(y\) versus \(x, y\) versus \(\log (x), \log (y)\) versus \(\log (x)\) and \(\frac{1}{y}\) versus \(\frac{1}{x}\). b. Which transformation considered in Part (a) does the best job of producing an approximately linear relationship? Use the selected transformation to predict lead content when distance is \(25 \mathrm{~m}\).

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.