- 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
See Arithmetic mean.
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain
Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
The variance of the conditional probability distribution of a random variable.
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
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.
Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.
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.
Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality
A probability distribution for a discrete random variable
Discrete random variable
A random variable with a inite (or countably ininite) range.
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 subset of a sample space.
A property of a collection of events that indicates that their union equals the sample space.
Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.
Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function
Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.