Winston Lin

Current Courses (Spring 2026)

• STAT1028 - Intro Business Stat

  The STAT 1028 honors section covers many of the same topics as STAT 1020 (such as multiple linear and logistic regression) and is designed for students who have studied calculus and are seeking a class with mathematical content. The class will assume good command of the material in MATH 1070 or MATH 1400 as a prerequisite. STAT 1028 is particularly recommended for students who are considering the concentration or minor in statistics and data science or other quantitative fields (such as quantitative finance).

  STAT1028001 ( Syllabus )

• STAT4300 - Probability

  Discrete and continuous sample spaces and probability; random variables, distributions, independence; expectation and generating functions; Markov chains and recurrence theory.

  STAT4300003 ( Syllabus )

All Courses

• STAT1018 - Intro Business Stat

  The STAT 1018 honors section, which fulfills the STAT 1010 requirement, offers an introduction to probability and statistics for students who have studied calculus and are seeking a class with mathematical content. The class will assume good command of the material in MATH 1070 or MATH 1400 as a prerequisite. STAT 1018 is particularly recommended for students who are considering the concentration or minor in statistics and data science or other quantitative fields (such as quantitative finance).

• STAT1028 - Intro Business Stat

  The STAT 1028 honors section covers many of the same topics as STAT 1020 (such as multiple linear and logistic regression) and is designed for students who have studied calculus and are seeking a class with mathematical content. The class will assume good command of the material in MATH 1070 or MATH 1400 as a prerequisite. STAT 1028 is particularly recommended for students who are considering the concentration or minor in statistics and data science or other quantitative fields (such as quantitative finance).

• STAT4300 - Probability

  Discrete and continuous sample spaces and probability; random variables, distributions, independence; expectation and generating functions; Markov chains and recurrence theory.