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Textbooks / Statistics / Elementary Statistics: A Step By Step Approach 9

Elementary Statistics: A Step By Step Approach 9th Edition - Solutions by Chapter

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

Elementary Statistics: A Step By Step Approach | 9th Edition - Solutions by Chapter

This expansive textbook survival guide covers the following chapters: 33. The full step-by-step solution to problem in Elementary Statistics: A Step By Step Approach were answered by , our top Statistics solution expert on 09/01/17, 05:46AM. Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985. Since problems from 33 chapters in Elementary Statistics: A Step By Step Approach have been answered, more than 115839 students have viewed full step-by-step answer. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9.

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

    In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

  • 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.

  • Average

    See Arithmetic mean.

  • Axioms of probability

    A set of rules that probabilities deined on a sample space must follow. See Probability

  • Bernoulli trials

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

  • Causal variable

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

  • 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 .

  • 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 variance.

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

  • Conidence interval

    If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

  • Continuous uniform random variable

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

  • 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

  • Defect

    Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

  • Defects-per-unit control chart

    See U chart

  • Dispersion

    The amount of variability exhibited by data

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Exponential random variable

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

  • 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.

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