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Solutions for Chapter 8.4: Point Estimation

Introduction to Probability and Statistics 1 | 14th Edition | ISBN: 9781133103752 | Authors: William Mendenhall Robert J. Beaver, Barbara M. Beaver

Full solutions for Introduction to Probability and Statistics 1 | 14th Edition

ISBN: 9781133103752

Introduction to Probability and Statistics 1 | 14th Edition | ISBN: 9781133103752 | Authors: William Mendenhall Robert J. Beaver, Barbara M. Beaver

Solutions for Chapter 8.4: Point Estimation

Solutions for Chapter 8.4
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Textbook: Introduction to Probability and Statistics 1
Edition: 14
Author: William Mendenhall Robert J. Beaver, Barbara M. Beaver
ISBN: 9781133103752

Since 23 problems in chapter 8.4: Point Estimation have been answered, more than 10508 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Introduction to Probability and Statistics 1, edition: 14. Chapter 8.4: Point Estimation includes 23 full step-by-step solutions. Introduction to Probability and Statistics 1 was written by and is associated to the ISBN: 9781133103752.

Key Statistics Terms and definitions covered in this textbook
  • Biased estimator

    Unbiased estimator.

  • C chart

    An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

  • Cause-and-effect diagram

    A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

  • Center line

    A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

  • Chi-square test

    Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

  • Conditional probability density function

    The probability density function of the conditional probability distribution of a continuous random variable.

  • Conditional probability mass function

    The probability mass function of the conditional probability distribution of a discrete random variable.

  • Control limits

    See Control chart.

  • Covariance matrix

    A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

  • Crossed factors

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

  • 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.

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Error of estimation

    The difference between an estimated value and the true value.

  • 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.

  • Exhaustive

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

  • Exponential random variable

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

  • F distribution.

    The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.

  • Finite population correction factor

    A term in the formula for the variance of a hypergeometric random variable.

  • Generating function

    A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function

  • Harmonic mean

    The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .

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