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Solutions for Chapter 13.1: Separable Partial Differential Equations

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 13.1: Separable Partial Differential Equations

Solutions for Chapter 13.1
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Textbook: Advanced Engineering Mathematics
Edition: 5
Author: Dennis G. Zill, Warren S. Wright
ISBN: 9781449691721

Chapter 13.1: Separable Partial Differential Equations includes 32 full step-by-step solutions. This expansive textbook survival guide covers the following chapters and their solutions. Advanced Engineering Mathematics was written by and is associated to the ISBN: 9781449691721. Since 32 problems in chapter 13.1: Separable Partial Differential Equations have been answered, more than 35045 students have viewed full step-by-step solutions from this chapter. 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.

  • Alternative hypothesis

    In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

  • Categorical data

    Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

  • Conditional probability

    The probability of an event given that the random experiment produces an outcome in another event.

  • Conditional probability distribution

    The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

  • Continuity correction.

    A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

  • Continuous random variable.

    A random variable with an interval (either inite or ininite) of real numbers for its range.

  • Contrast

    A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

  • Cook’s distance

    In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

  • Decision interval

    A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.

  • Deming

    W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

  • Deming’s 14 points.

    A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Design matrix

    A matrix that provides the tests that are to be conducted in an experiment.

  • Exhaustive

    A property of a collection of events that indicates that their union equals the sample space.

  • Experiment

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

  • False alarm

    A signal from a control chart when no assignable causes are present

  • Fisher’s least signiicant difference (LSD) method

    A series of pair-wise hypothesis tests of treatment means in an experiment to determine which means differ.

  • Fractional factorial experiment

    A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

  • Geometric random variable

    A discrete random variable that is the number of Bernoulli trials until a success occurs.

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