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Algorithms 1st Edition - Solutions by Chapter

Algorithms | 1st Edition | ISBN: 9780073523408 | Authors: Sanjoy Dasgupta Algorithms, Christos H. Papadimitriou Algorithms, Umesh Vazirani Algorithms

Full solutions for Algorithms | 1st Edition

ISBN: 9780073523408

Algorithms | 1st Edition | ISBN: 9780073523408 | Authors: Sanjoy Dasgupta Algorithms, Christos H. Papadimitriou Algorithms, Umesh Vazirani Algorithms

Algorithms | 1st Edition - Solutions by Chapter

Since problems from 11 chapters in Algorithms have been answered, more than 3096 students have viewed full step-by-step answer. This expansive textbook survival guide covers the following chapters: 11. The full step-by-step solution to problem in Algorithms were answered by Patricia, our top Statistics solution expert on 03/08/18, 07:35PM. Algorithms was written by Patricia and is associated to the ISBN: 9780073523408. This textbook survival guide was created for the textbook: Algorithms , edition: 1.

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.

  • 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.

  • 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.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Central composite design (CCD)

    A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.

  • Conditional mean

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

  • Contingency table.

    A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

  • Continuity correction.

    A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

  • Contour plot

    A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

  • Correlation coeficient

    A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

  • 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.

  • Defect concentration diagram

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

  • 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.

  • Expected value

    The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

  • 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.

  • Fraction defective

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

  • Goodness of fit

    In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.

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