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Solutions for Chapter 4: SCATTER DIAGRAMS AND CORRELATION

Statistics: Informed Decisions Using Data | 4th Edition | ISBN: 9780321757272 | Authors: Michael Sullivan, III

Full solutions for Statistics: Informed Decisions Using Data | 4th Edition

ISBN: 9780321757272

Statistics: Informed Decisions Using Data | 4th Edition | ISBN: 9780321757272 | Authors: Michael Sullivan, III

Solutions for Chapter 4: SCATTER DIAGRAMS AND CORRELATION

Solutions for Chapter 4
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Textbook: Statistics: Informed Decisions Using Data
Edition: 4
Author: Michael Sullivan, III
ISBN: 9780321757272

Since 84 problems in chapter 4: SCATTER DIAGRAMS AND CORRELATION have been answered, more than 162465 students have viewed full step-by-step solutions from this chapter. Chapter 4: SCATTER DIAGRAMS AND CORRELATION includes 84 full step-by-step solutions. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. 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

  • Asymptotic relative eficiency (ARE)

    Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

  • Attribute

    A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

  • Causal variable

    When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

  • Central limit theorem

    The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

  • Conditional variance.

    The variance of the conditional probability distribution of a random variable.

  • Conidence coeficient

    The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

  • Control chart

    A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

  • Control limits

    See Control chart.

  • Cumulative distribution function

    For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

  • Curvilinear regression

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

  • Deming

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

  • Discrete uniform random variable

    A discrete random variable with a inite range and constant probability mass function.

  • Distribution function

    Another name for a cumulative distribution function.

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • Exponential random variable

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

  • Fraction defective control chart

    See P chart

  • 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.

  • Gamma function

    A function used in the probability density function of a gamma random variable that can be considered to extend factorials

  • 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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