Probability and Statistics for Computer Scientists
Versandkostenfrei!
Nicht lieferbar
Weitere Ausgaben:
Table of contents:Table of contents not yet availableEmphasizing methodology and applications rather than rigorous mathematical theory, Probability and Statistics for Computer Scientists presents the elementary rules of probability and distributions, stochastic processes, and Markov chains. The author introduces tools used in queuing theory, including discrete-time and continuous-time queuing systems, and also covers such topics as statistical interference, estimation and testing, regression, and model fitting. This text fully satisfies the ABET requirements. It is designed for a one-semester ...
Table of contents:
Table of contents not yet available
Emphasizing methodology and applications rather than rigorous mathematical theory, Probability and Statistics for Computer Scientists presents the elementary rules of probability and distributions, stochastic processes, and Markov chains. The author introduces tools used in queuing theory, including discrete-time and continuous-time queuing systems, and also covers such topics as statistical interference, estimation and testing, regression, and model fitting. This text fully satisfies the ABET requirements. It is designed for a one-semester first course for junior/senior level undergraduate computer science students with background in calculus and some familiarity with linear algebra.
Emphasizing methodology and applications rather than rigorous mathematical theory, Probability and Statistics for Computer Scientists presents the elementary rules of probability and distributions, stochastic processes, and Markov chains. The author introduces tools used in queuing theory, including discrete-time and continuous-time queuing systems, and also covers such topics as statistical interference, estimation and testing, regression, and model fitting. This text fully satisfies the ABET requirements. It is designed for a one-semester first course for junior/senior level undergraduate computer science students with background in calculus and some familiarity with linear algebra.
Table of contents not yet available
Emphasizing methodology and applications rather than rigorous mathematical theory, Probability and Statistics for Computer Scientists presents the elementary rules of probability and distributions, stochastic processes, and Markov chains. The author introduces tools used in queuing theory, including discrete-time and continuous-time queuing systems, and also covers such topics as statistical interference, estimation and testing, regression, and model fitting. This text fully satisfies the ABET requirements. It is designed for a one-semester first course for junior/senior level undergraduate computer science students with background in calculus and some familiarity with linear algebra.
Emphasizing methodology and applications rather than rigorous mathematical theory, Probability and Statistics for Computer Scientists presents the elementary rules of probability and distributions, stochastic processes, and Markov chains. The author introduces tools used in queuing theory, including discrete-time and continuous-time queuing systems, and also covers such topics as statistical interference, estimation and testing, regression, and model fitting. This text fully satisfies the ABET requirements. It is designed for a one-semester first course for junior/senior level undergraduate computer science students with background in calculus and some familiarity with linear algebra.