Package: Numerical Methods For Engineers With 2 Semester Connect Access Card
7th Edition
ISBN: 9781259279911
Author: Steven Chapra
Publisher: McGraw-Hill Education
expand_more
expand_more
format_list_bulleted
Concept explainers
Textbook Question
Chapter 17, Problem 28P
An object is suspended in a wind tunnel and the force measured for various levels of wind velocity. The results are tabulated below.
v, m/s | 10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 |
F, N | 25 | 70 | 380 | 550 | 610 | 1220 | 830 | 1450 |
Use least-squares regression to fit these data with
(a) A straight line,
(b) A power equation based on log transformations, and
(c) A power model based on nonlinear regression. Display the results graphically.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
The following table shows the rate R of vehicular involvement in traffic accidents (per 100,000,000 vehicle-miles) as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night on urban streets.
Speed s
Accident rate R
20
1600
25
600
30
200
35
300
40
800
45
1250
(A) Use regression to find a quadratic model for the data. (Round the regression parameters to two decimal places.)
R =
The table below shows enrollment,† in millions of people, in private colleges in the United States during the years from 2004 through 2008.
Date
Enrollment in millions
2004
4.29
2005
4.47
2006
4.58
2007
4.76
2008
5.13
Find the equation of the regression line model for college enrollment as a function of time. (Let t be the number of years since 2004 and E the enrollment in private colleges, in millions. Round regression line parameters to two decimal places.)
The following table shows the rate R of vehicular involvement in traffic accidents (per 100,000,000 vehicle-miles) as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night on urban streets.
Speed s
Accident rate R
20
1550
25
700
30
200
35
250
40
650
45
1300
(a) Use regression to find a quadratic model for the data. (Round the regression parameters to two decimal places.)
R =_______
(c) At what speed is vehicular involvement in traffic accidents (for commercial vehicles driving at night on urban streets) at a minimum? (Round your answer to the nearest whole number.)
Chapter 17 Solutions
Package: Numerical Methods For Engineers With 2 Semester Connect Access Card
Ch. 17 - Given these data 8.8 9.5 9.8 9.4 10.0 9.4 10.1 9.2...Ch. 17 - Given these data 29.65 28.55 28.65 30.15 29.35...Ch. 17 - 17.3 Use least-squares regression to fit a...Ch. 17 - 17.4 Use least-squares regression to fit a...Ch. 17 - 17.5 Using the same approach as was employed to...Ch. 17 - Use least-squares regression to fit a straight...Ch. 17 - Fit the following data with (a) A...Ch. 17 - Fit the following data with the power model...Ch. 17 - 17.9 Fit an exponential model...Ch. 17 - 17.10 Rather than using the base-e exponential...
Ch. 17 - 17.11 Beyond the examples in Fig. 17.10, there are...Ch. 17 - 17.12 An investigator has reported the data...Ch. 17 - An investigator has reported the data tabulated...Ch. 17 - 17.14 It is known that the data tabulated below...Ch. 17 - 17.15 The following data are...Ch. 17 - Given these data x 5 10 15 20 25 30 35 40 45 50 y...Ch. 17 - 17.17 Fit a cubic equation to the following...Ch. 17 - Use multiple linear regression to fit x1 0 1 1 2 2...Ch. 17 - Use multiple linear regression to fit x1 0 0 1 2 0...Ch. 17 - Use nonlinear regression to fit a parabola to the...Ch. 17 - 17.21 Use nonlinear regression to fit a...Ch. 17 - 17.22 Recompute the regression fits from Probs....Ch. 17 - Develop, debug, and test a program in either a...Ch. 17 - A material is tested for cyclic fatigue failure...Ch. 17 - The following data show the relationship between...Ch. 17 - 17.26 The data below represents the bacterial...Ch. 17 - The concentration of E. coli bacteria in a...Ch. 17 - 17.28 An object is suspended in a wind tunnel and...Ch. 17 - 17.29 Fit a power model to the data from Prob....Ch. 17 - Derive the least-squares fit of the following...Ch. 17 - 17.31 In Prob. 17.11 we used transformations to...
Additional Math Textbook Solutions
Find more solutions based on key concepts
(a) Show that (x) = x2 is an explicit solution to xdydx = 2y on the interval (, ). (b) Show that (x) = ex x is...
Fundamentals of Differential Equations (9th Edition)
|4.2| = ?
Basic Technical Mathematics
Analytic Functions. Find fz=ux,y+ivx,y with u or v as given. Check by the Cauchy Reimann equations for analyti...
Advanced Engineering Mathematics
The possible names of the line containing the points.
Geometry For Enjoyment And Challenge
To evaluate the expression
Pre-Algebra Student Edition
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, advanced-math and related others by exploring similar questions and additional content below.Similar questions
- The table below shows the traffic fatality rate R, in fatalities per 100 million vehicle miles traveled, t years after 2010.† Find the equation of the regression line for R as a function of t. (Round regression line parameters to two decimal places.) t = years since 2010 R = rate 0 1.11 1 1.10 2 1.14 3 1.09 4 1.07arrow_forwardThe following table shows the rate R of vehicular involvement in traffic accidents (per 100,000,000 vehicle-miles) as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night on urban streets. Speed s Accident rate R 20 1500 25 700 30 250 35 300 40 750 45 1400 (a) Use regression to find a quadratic model for the data. (Round the regression parameters to two decimal places.) R = 7.79s2−514.36s+8733.57 (b) Calculate R(70). (Round your answer to two decimal places.) R(70) = Explain what your answer means in practical terms. Commercial vehicles driving at night on urban streets at miles per hour have traffic accidents at a rate of per 100,000,000 vehicle miles.arrow_forwardThe table below shows enrollment,† in millions of people, in private colleges in the United States during the years from 2004 through 2008. date enrollment in millions 2004 4.29 2005 4.47 2006 4.58 2007 4.76 2008 5.13 (a) Find the equation of the regression line model for college enrollment as a function of time. (Let t be the number of years since 2004 and E the enrollment in private colleges, in millions. Round regression line parameters to two decimal places.) E(t)= Add the graph of the regression line to the data plot. (b) Explain the meaning of the slope of the line you found in part (a). The slope of the regression line is ?.... , and this means that every year the enrollment in American private colleges increased by about ?.... million. (c) Express, using functional notation, the enrollment in American private colleges in 2013. E ...? ( ) Estimate that value. (Round your answer to two decimal places.) ?.... million (d) Enrollment in American private…arrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- Elementary Linear Algebra (MindTap Course List)AlgebraISBN:9781305658004Author:Ron LarsonPublisher:Cengage LearningLinear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningFunctions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage
Elementary Linear Algebra (MindTap Course List)
Algebra
ISBN:9781305658004
Author:Ron Larson
Publisher:Cengage Learning
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:9781133382119
Author:Swokowski
Publisher:Cengage
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY