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Solutions for Chapter Chapter 7: Random Variables and Probability Distributions

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition | ISBN: 9780495118732 | Authors: Roxy Peck, Chris Olsen, Jay L. Devore

Full solutions for Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition

ISBN: 9780495118732

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition | ISBN: 9780495118732 | Authors: Roxy Peck, Chris Olsen, Jay L. Devore

Solutions for Chapter Chapter 7: Random Variables and Probability Distributions

Solutions for Chapter Chapter 7
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Textbook: Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW)
Edition: 3
Author: Roxy Peck, Chris Olsen, Jay L. Devore
ISBN: 9780495118732

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) was written by and is associated to the ISBN: 9780495118732. Chapter Chapter 7: Random Variables and Probability Distributions includes 128 full step-by-step solutions. This expansive textbook survival guide covers the following chapters and their solutions. Since 128 problems in chapter Chapter 7: Random Variables and Probability Distributions have been answered, more than 17987 students have viewed full step-by-step solutions from this chapter. This textbook survival guide was created for the textbook: Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW), edition: 3.

Key Statistics Terms and definitions covered in this textbook
  • a-error (or a-risk)

    In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

  • Attribute control chart

    Any control chart for a discrete random variable. See Variables control chart.

  • Average

    See Arithmetic mean.

  • Backward elimination

    A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

  • Bias

    An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

  • Binomial random variable

    A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

  • 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.

  • Combination.

    A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

  • 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 value(s)

    The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

  • Cumulative sum control chart (CUSUM)

    A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

  • Deming

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

  • Discrete distribution

    A probability distribution for a discrete random variable

  • Discrete uniform random variable

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

  • Error propagation

    An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

  • 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.

  • 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.

  • Gamma random variable

    A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

  • 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

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