Computing and Statistical Data Analysis (CSDA | INR7001U)
Description: This course aims to introduce students to
programming techniques using the C++ language on a Unix platform. It
will also introduce students to techniques of probability and
statistical data analysis and they will study applications of data
analysis using C++ based computing tools.
- Introduction to C++ and the Unix operating system.
- Variables, types and expressions.
- Functions and the basics of procedural programming.
- I/O and files.
- Basic control structures: branches and loops.
- Arrays, strings, pointers.
- Basic concepts of object oriented programming.
- Probability: definition and interpretation, random variables, probability density functions, expectation values, transformation of variables, error propagation, examples of probability functions.
- The Monte Carlo method: random number generators, transformation method, acceptance-rejection method.
- Statistical tests: significance and power, choice of critical region, goodness-of-fit.
- Parameter estimation: samples, estimators, bias, method of maximum likelihood, method of least squares, interval estimation, setting limits, unfolding.
- Introduction to C++ and the Unix operating system.
- Variables, types and expressions.
- Functions and the basics of procedural programming.
- I/O and files.
- Basic control structures: branches and loops.
- Arrays, strings, pointers.
- Basic concepts of object oriented programming.
- Probability: definition and interpretation, random variables, probability density functions, expectation values, transformation of variables, error propagation, examples of probability functions.
- The Monte Carlo method: random number generators, transformation method, acceptance-rejection method.
- Statistical tests: significance and power, choice of critical region, goodness-of-fit.
- Parameter estimation: samples, estimators, bias, method of maximum likelihood, method of least squares, interval estimation, setting limits, unfolding.
