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Solutions for Chapter 9.8: Line Integrals

Advanced Engineering Mathematics | 5th Edition | ISBN: 9781449691721 | Authors: Dennis G. Zill, Warren S. Wright

Full solutions for Advanced Engineering Mathematics | 5th Edition

ISBN: 9781449691721

Advanced Engineering Mathematics | 5th Edition | ISBN: 9781449691721 | Authors: Dennis G. Zill, Warren S. Wright

Solutions for Chapter 9.8: Line Integrals

Solutions for Chapter 9.8
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Textbook: Advanced Engineering Mathematics
Edition: 5
Author: Dennis G. Zill, Warren S. Wright
ISBN: 9781449691721

Chapter 9.8: Line Integrals includes 42 full step-by-step solutions. Since 42 problems in chapter 9.8: Line Integrals have been answered, more than 33044 students have viewed full step-by-step solutions from this chapter. Advanced Engineering Mathematics was written by and is associated to the ISBN: 9781449691721. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Advanced Engineering Mathematics , edition: 5.

Key Statistics Terms and definitions covered in this textbook
  • 2 k factorial experiment.

    A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

  • 2 k p - factorial experiment

    A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

  • a-error (or a-risk)

    In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

  • All possible (subsets) regressions

    A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

  • Assignable cause

    The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

  • Average run length, or ARL

    The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

  • Backward elimination

    A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

  • Central composite design (CCD)

    A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.

  • Components of variance

    The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

  • Correction factor

    A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

  • Curvilinear regression

    An expression sometimes used for nonlinear regression models or polynomial regression models.

  • Deining relation

    A subset of effects in a fractional factorial design that deine the aliases in the design.

  • Density function

    Another name for a probability density function

  • Dispersion

    The amount of variability exhibited by data

  • Eficiency

    A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

  • Error variance

    The variance of an error term or component in a model.

  • Estimator (or point estimator)

    A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

  • Expected value

    The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

  • Exponential random variable

    A series of tests in which changes are made to the system under study

  • Hat matrix.

    In multiple regression, the matrix H XXX X = ( ) ? ? -1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .

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