Solutions for Chapter 5.3: Elementary Statistics: A Step By Step Approach 9th Edition

Elementary Statistics: A Step By Step Approach | 9th Edition | ISBN: 9780073534985 | Authors: Allan Bluman

Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition

ISBN: 9780073534985

Elementary Statistics: A Step By Step Approach | 9th Edition | ISBN: 9780073534985 | Authors: Allan Bluman

Solutions for Chapter 5.3

Solutions for Chapter 5.3
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Textbook: Elementary Statistics: A Step By Step Approach
Edition: 9th
Author: Allan Bluman
ISBN: 9780073534985

Elementary Statistics: A Step By Step Approach was written by Sieva Kozinsky and is associated to the ISBN: 9780073534985. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9th. Since 21 problems in chapter 5.3 have been answered, more than 40419 students have viewed full step-by-step solutions from this chapter. Chapter 5.3 includes 21 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
  • 2 k factorial experiment.

    A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

  • 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).

  • Average

    See Arithmetic mean.

  • Bivariate normal distribution

    The joint distribution of two normal random variables

  • Box plot (or box and whisker plot)

    A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

  • Causal variable

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

  • Cause-and-effect diagram

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

  • 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.

  • Conditional probability density function

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

  • 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

  • Conditional probability mass function

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

  • Correlation

    In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

  • Defect concentration diagram

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

  • 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.

  • Fraction defective

    In statistical quality control, that portion of a number of units or the output of a process that is defective.

  • Fractional factorial experiment

    A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

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