- Chapter 0: Prologue
- Chapter 1: Algorithms with numbers
- Chapter 10: Quantum algorithms
- Chapter 2: Divide-and-conquer algorithms
- Chapter 3: Decompositions of graphs
- Chapter 4: Paths in graphs
- Chapter 5: Greedy algorithms
- Chapter 6: Dynamic programming
- Chapter 7: Linear programming and reductions
- Chapter 8: NP-complete problems
- Chapter 9: Coping with NP-completeness
Algorithms 1st Edition - Solutions by Chapter
Full solutions for Algorithms | 1st Edition
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test
Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.
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.
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.
Coeficient of determination
See R 2 .
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.
Formulas used to determine the number of elements in sample spaces and events.
Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.
A subset of effects in a fractional factorial design that deine the aliases in the design.
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.
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
Error of estimation
The difference between an estimated value and the true value.
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.
A series of tests in which changes are made to the system under study
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.
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.
Fraction defective control chart
See P chart
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.