EE5373: Data Modeling Using R

1 Credit

Introduction to data modeling and the R language programming. Multi-factor linear regression modeling. Residual analysis and model quality evaluation. Response prediction. Training and testing. Integral lab. An introductory course in probability and statistics is suggested but not required; basic programming skills in some high-level programming language, such as C/C++, Java, Fortran, etc also suggested.

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A Average (3.843)Most Common: A (78%)

This total also includes data from semesters with unknown instructors.

154 students
WFDCBA
  • 5.66

    /6

    Recommend
  • 5.45

    /6

    Effort
  • 5.69

    /6

    Understanding
  • 4.93

    /6

    Interesting
  • 5.57

    /6

    Activities


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