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Fall 2020
Mar 07, 2021
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Information Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. The Schedule Type links will be available only when the schedule of classes is available for the selected term.

STAT 54500 - Introduction To Computational Statistics
Credit Hours: 3.00. This introductory course covers the fundamentals of computing for statistics and data analysis. It starts with a brief overview of programming using a general purpose compiled language (C) and a statistics-oriented interpreted language (R). The course proceeds to cover data structures and algorithms that are directly relevant to statistics and data analysis and concludes with a computing-oriented introduction to selected statistical methods. A significant part of the course involves programming and hands-on experimentation demonstrating the covered techniques, ration, and Markov chain Monte Carlo methods. Typically offered Fall.
3.000 Credit hours

Syllabus Available
Levels: Graduate, Professional, Undergraduate
Schedule Types: Distance Learning, Lecture
All Sections for this Course

Offered By: College of Science
Department: Statistics

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette

Learning Outcomes: 1. Given a straightforward data manipulation problem, decide on what elementary data structures to use, write down an algorithm for a solution as a pseudocode, and analyze its computational complexity. 2. Implement an algorithm using C and/or R code, understand, modify, and if needed perform basic debugging of the existing code. 3. Understand and implement the computational techniques of numerical optimization, matrix manipulation, sampling, logistic regression, and EM algorithm.



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