×
Log in to StudySoup
Get Full Access to Statistics - Textbook Survival Guide
Join StudySoup for FREE
Get Full Access to Statistics - Textbook Survival Guide

Solutions for Chapter 2: Probability

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 2: Probability

Solutions for Chapter 2
4 5 0 287 Reviews
12
3
Textbook: Mathematical Statistics with Applications
Edition: 7
Author: Dennis Wackerly; William Mendenhall; Richard L. Scheaffer
ISBN: 9780495110811

Since 163 problems in chapter 2: Probability have been answered, more than 155216 students have viewed full step-by-step solutions from this chapter. 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. Chapter 2: Probability includes 163 full step-by-step solutions. This textbook survival guide was created for the textbook: Mathematical Statistics with Applications , edition: 7.

Key Statistics Terms and definitions covered in this textbook
  • Adjusted R 2

    A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • Bayes’ theorem

    An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).

  • Biased estimator

    Unbiased estimator.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Categorical data

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

  • Comparative experiment

    An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

  • 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

  • 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.

  • Defects-per-unit control chart

    See U chart

  • 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.

  • Dispersion

    The amount of variability exhibited by data

  • Distribution function

    Another name for a cumulative distribution function.

  • Eficiency

    A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

  • Error of estimation

    The difference between an estimated value and the true value.

  • Exponential random variable

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

  • Frequency distribution

    An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

  • Gaussian distribution

    Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

  • 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 .

×
Log in to StudySoup
Get Full Access to Statistics - Textbook Survival Guide
Join StudySoup for FREE
Get Full Access to Statistics - Textbook Survival Guide
×
Reset your password