# Statistics and Computer Science

This major is sponsored jointly by the Departments of Statistics and Computer Science. The Statistics and Computer Science major is designed for students who would like a strong foundation in computer science, coupled with significant advanced coursework in statistics. The major prepares students for professional or graduate work in statistics and computer science, and for applications of computing in which knowledge of statistics is particularly important, such as data mining and machine learning. See also Computer Science, Mathematics, Mathematics and Computer Science, and Statistics.

## Major in Sciences and Letters Curriculum

E-mail: stat-office@illinois.edu or academic@cs.illinois.edu

Degree title: Bachelor of Science in Liberal Arts and Sciences

Minimum required major and supporting course work normally equates to 68-69 hours

General education: Students must complete the Campus General Education requirements including the campus general education language requirement.

Twelve hours of 300 and 400-level courses must be taken on this campus.

Minimum hours required for graduation: 120 hours

Departmental distinction: To graduate with distinction requires a specified minimum grade point average in all Computer Science, Statistics, and Mathematics courses listed below. A GPA of 3.25 is required for Distinction, 3.5 for High Distinction, and 3.75 for Highest Distinction.

Code | Title | Hours |
---|---|---|

CS 100 | Freshman Orientation (recommended) | 0-1 |

Calculus through MATH 241 - Calculus III | 11-12 | |

MATH 415 | Applied Linear Algebra | 3 |

Required Computer Science Foudation: | 32 | |

Intro to Computer Science | ||

Discrete Structures | ||

Software Design Studio | ||

Data Structures | ||

Computer Architecture | ||

System Programming | ||

Numerical Methods I | ||

Introduction to Algorithms & Models of Computation | ||

Progrmg Languages & Compilers | ||

Required Probability and Statistics Foundation: | 10 | |

Statistics and Probability I ^{1} | ||

Statistics and Probability II | ||

Statistical Computing | ||

At least four other statistics, computer science, or mathematics courses, with at least one chosen from each of the following groups: | 12 | |

Group I: Statistical Methods | ||

Statistical Analysis | ||

Biostatistics | ||

Probability & Statistics for Computer Science | ||

Group II: Mathematical Analysis and Modeling | ||

Fundamental Mathematics | ||

Differential Equations | ||

Elementary Real Analysis | ||

Real Variables | ||

Group III: Computational Application Areas | ||

Statistics Programming Methods | ||

Text Information Systems | ||

Database Systems | ||

Introduction to Data Mining | ||

Machine Learning | ||

Stochastic Processes & Applic | ||

Simulation | ||

Group IV: Statistical Analysis and Modeling | ||

Methods of Applied Statistics | ||

Applied Regression and Design | ||

Sampling and Categorical Data | ||

Advanced Data Analysis |

^{1} | Students should take a course from Group I before taking |