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Solutions for Chapter Chapter 5: Regression

Full solutions for The Basic Practice of Statistics | 4th Edition

ISBN: 9780716774785

Solutions for Chapter Chapter 5: Regression

Solutions for Chapter Chapter 5
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Textbook: The Basic Practice of Statistics
Edition: 4
Author: David S. Moore
ISBN: 9780716774785

This expansive textbook survival guide covers the following chapters and their solutions. Since 50 problems in chapter Chapter 5: Regression have been answered, more than 10673 students have viewed full step-by-step solutions from this chapter. The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785. Chapter Chapter 5: Regression includes 50 full step-by-step solutions. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4.

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).

  • 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.

  • 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.

  • Bernoulli trials

    Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

  • Biased estimator

    Unbiased estimator.

  • Bimodal distribution.

    A distribution with two modes

  • Causal variable

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

  • Central tendency

    The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

  • Chi-square (or chi-squared) random variable

    A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.

  • Coeficient of determination

    See R 2 .

  • Conditional mean

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

  • 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.

  • Counting techniques

    Formulas used to determine the number of elements in sample spaces and events.

  • 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

  • Discrete random variable

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

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Finite population correction factor

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

  • 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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