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Solutions for Chapter 11: Simple Linear Regression and Correlation

Applied Statistics and Probability for Engineers | 5th Edition | ISBN: 9780470053041 | Authors: Douglas C. Montgomery, George C. Runger

Full solutions for Applied Statistics and Probability for Engineers | 5th Edition

ISBN: 9780470053041

Applied Statistics and Probability for Engineers | 5th Edition | ISBN: 9780470053041 | Authors: Douglas C. Montgomery, George C. Runger

Solutions for Chapter 11: Simple Linear Regression and Correlation

Solutions for Chapter 11
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Textbook: Applied Statistics and Probability for Engineers
Edition: 5
Author: Douglas C. Montgomery, George C. Runger
ISBN: 9780470053041

Chapter 11: Simple Linear Regression and Correlation includes 104 full step-by-step solutions. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers, edition: 5. Since 104 problems in chapter 11: Simple Linear Regression and Correlation have been answered, more than 22565 students have viewed full step-by-step solutions from this chapter. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780470053041. This expansive textbook survival guide covers the following chapters and their solutions.

Key Statistics Terms and definitions covered in this textbook
  • Acceptance region

    In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

  • Arithmetic mean

    The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

  • 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.

  • Bayes’ estimator

    An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

  • Biased estimator

    Unbiased estimator.

  • Central tendency

    The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

  • Continuous uniform random variable

    A continuous random variable with range of a inite interval and a constant probability density function.

  • Control limits

    See Control chart.

  • Convolution

    A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

  • Critical region

    In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

  • Crossed factors

    Another name for factors that are arranged in a factorial experiment.

  • Curvilinear regression

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

  • Deming’s 14 points.

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

  • Density function

    Another name for a probability density function

  • Distribution function

    Another name for a cumulative distribution function.

  • Exponential random variable

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

  • Extra sum of squares method

    A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

  • False alarm

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

  • Fraction defective

    In statistical quality control, that portion of a number of units or the output of a process that is defective.

  • Geometric random variable

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

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