Course: AMT 377 2.0 Computational Statistics (Compulsory)
Course content:
Introduction to R; Objects, their modes and attributes (Vectors, Matrices, Lists, Data Frames, Factors), Data Input/Output, descriptive methods, R graphs/ Tables, Pattern data, arbitrary data, data from probability distributions, IF, ELSE, Logical operations, FOR and WHILE loops, Working with different R packages that are used to different tests and operations, Parametric and non-parametric tests for hypothesis testing on mean and median, Confidence intervals, linear models, extracting data from outputs, empirical power of tests, Functions and arguments, provide a function as a solution for a problem, Simulation studies
Recommended Readings:
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- Crawley, M.J. (2007). The R book. John Willey & Sons.
- Chambers,J.M. (2008). Software for Data Analysis: Programming with R. Springer.
- Rizzo,M.L. (2007). Statistical computing with R. Chapman & Hall.