SCIENTIFIC PROGRAMMING AND SIMULATION 12.5
Professor A J Guttmann.
Semester 1
39 lectures (three a week), 24 hours practical (two hours a week), 12 x 1-hour tutorials and 12 hours project work.
On completion of this subject, students should:
Comprehend:
the syntax of a programming language;
the terminology of probability and the principles of probability modelling.
Have developed:
the ability to read, write and adapt computer programs;
skills in reformulation of problems in a form suitable for computer solution;
the ability to use established numerical methods;
the ability to carry out probability calculations using standard distributions;
the ability to make an appropriate choice of model for standard situations;
the ability to write programs to simulate simple probability models.
Appreciate:
the structure of a programming language, its potential and limitations;
the application of probability modelling in describing the real world;
the concept of randomness.
Introduction to programming: algorithms, simple data types, assignment, conditionals, iteration, functions and procedures, complex data types, array processing. Numerical methods: number representation, errors, numerical integration, solution of linear and nonlinear equations. Probability: basic probability theory, conditional probability and independence, law of total probability and Bayes' theorem. Elementary distribution theory: cumulative distribution function and quantiles; probability mass function and probability density function. Discrete and continuous distributions - using binomial and normal distributions as examples. Uniform number generators. Simulation of observations on a given distribution. Simulation of probability models. Application of the computer to simulation.
Up to 26 pages of written assignments; project work as required; and up to three hours of end-of-semester written examination.
Students may not gain credit for both Mathematical Sciences 617-141 and any of 617-142, 617-160 (1995 Handbook), 617-170 (1994 Handbook), 619-100 or 619-101.
SCIENTIFIC PROGRAMMING AND SIMULATION 12.5
Professor A J Guttmann.
Semester 1
39 lectures (three a week), 24 hours practical (two hours a week), 12 x 1-hour tutorials and 12 hours project work.
On completion of this subject, students should:
Comprehend:
the syntax of a programming language;
the terminology of probability and the principles of probability modelling.
Have developed:
the ability to read, write and adapt computer programs;
skills in reformulation of problems in a form suitable for computer solution;
the ability to use established numerical methods;
the ability to carry out probability calculations using standard distributions;
the ability to make an appropriate choice of model for standard situations;
the ability to write programs to simulate simple probability models.
Appreciate:
the structure of a programming language, its potential and limitations;
the application of probability modelling in describing the real world;
the concept of randomness.
Introduction to programming Algorithms, simple data types, assignment, conditionals, iteration, functions and procedures, complex data types, array processing. Numerical methods Number representation, errors, numerical integration, solution of linear and nonlinear equations. Probability Basic probability theory. Conditional probability and independence. Law of total probability and Bayes' theorem. Elementary distribution theory: cumulative distribution function and quantiles; probability mass function and probability density function. Discrete and continuous distributions - using binomial and normal distributions as examples. Uniform number generators. Simulation of observations on a given distribution. Simulation of probability models. Application of the computer to simulation.
Up to 26 pages of written assignments; project work as required; and up to three hours of end-of-semester written examination.
Students may not gain credit for both Mathematical Sciences 617-141 and any of 617-142, 617-160 (1995 Handbook), 617-170 (1994 Handbook), 619-100 or 619-101.
SCIENTIFIC PROGRAMMING AND SIMULATION Students may not gain credit for both Mathematical Sciences 617-141 and any of 617-142, 617-160 (1995 Handbook), 617-170 (1994 Handbook), 619-100 or 619-101.
12.5
Professor A J Guttmann.
First semester.
39 lectures (three each week), 24 hours practical (two hours each week), 12 1-hour tutorials and 12 hours project work.
On completion of this subject, students should:
Comprehend:
the syntax of a programming language;
the terminology of probability and the principles of probability modelling.
Have developed:
the ability to read, write and adapt computer programs;
skills in reformulation of problems in a form suitable for computer solution;
the ability to use established numerical methods;
the ability to carry out probability calculations using standard distributions;
the ability to make an appropriate choice of model for standard situations;
the ability to write programs to simulate simple probability models.
Appreciate:
the structure of a programming language, its potential and limitations;
the application of probability modelling in describing the real world;
the concept of randomness.
Introduction to programming Algorithms, simple data types, assignment, conditionals, iteration, functions and procedures, complex data types, array processing. Numerical methods Number representation, errors, numerical integration, solution of linear and nonlinear equations. Probability Basic probability theory. Conditional probability and independence. Law of total probability and Bayes' theorem. Elementary distribution theory: cumulative distribution function and quantiles; probability mass function and probability density function. Discrete and continuous distributions - using binomial and normal distributions as examples. Uniform number generators. Simulation of observations on a given distribution. Simulation of probability models. Application of the computer to simulation.
Up to 26 pages of written assignments; project work as required; and up to three hours of end-of-semester written examination.