Solutions for Chapter 8: Estimation

Mathematical Statistics with Applications | 7th Edition | ISBN: 9780495110811 | Authors: Dennis Wackerly, William Mendenhall Richard L. Scheaffer

Full solutions for Mathematical Statistics with Applications | 7th Edition

ISBN: 9780495110811

Mathematical Statistics with Applications | 7th Edition | ISBN: 9780495110811 | Authors: Dennis Wackerly, William Mendenhall Richard L. Scheaffer

Solutions for Chapter 8: Estimation

Solutions for Chapter 8
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Textbook: Mathematical Statistics with Applications
Edition: 7th
Author: Dennis Wackerly, William Mendenhall Richard L. Scheaffer
ISBN: 9780495110811

Since 121 problems in chapter 8: Estimation have been answered, more than 77305 students have viewed full step-by-step solutions from this chapter. This textbook survival guide was created for the textbook: Mathematical Statistics with Applications , edition: 7th. Chapter 8: Estimation includes 121 full step-by-step solutions. Mathematical Statistics with Applications was written by and is associated to the ISBN: 9780495110811. This expansive textbook survival guide covers the following chapters and their solutions.

Key Statistics Terms and definitions covered in this textbook
  • Addition rule

    A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

  • 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

  • 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.

  • 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.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • 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.

  • Continuous uniform random variable

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

  • 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.

  • Defect concentration diagram

    A quality tool that graphically shows the location of defects on a part or in a process.

  • Degrees of freedom.

    The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

  • Density function

    Another name for a probability density function

  • Discrete random variable

    A random variable with a inite (or countably ininite) range.

  • Distribution function

    Another name for a cumulative distribution function.

  • Error variance

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

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • 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.

  • Forward selection

    A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

  • Generator

    Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

  • 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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