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MATH 472 Syllabus

Data Science

Revised: October 2021

Course Description

Introduction to a high-level language, exploring and manipulating data, functions and basic coding, deterministic and stochastic modeling, concepts of projects and code management, databases, data collection and statistical inference. Prerequisite: MATH 270 or MATH 370.
Three semester hours.

Student Learning Objectives

By the end of the course students will be able to:

  • Compose a program to manipulate data into a usable form for analysis
  • Build functions that simplify a coding task
  • Develop models that summarize data
  • Utilize databases to answer research questions
  • Choose an appropriate statistical inference procedure

Text

Determined by instructor, but one choice might be:

  • Hadley Wickham and Garrett Grolemund, R for Data Science, First Edition, by O'Reilly Media.

Grading Procedure

Grading procedures and factors influencing course grade are left to the discretion of individual instructors, subject to general university policy.

Attendance Policy

Attendance policy is left to the discretion of individual instructors, subject to general university policy.

Course Outline

  • Unit I: Explore (3 weeks) 鈥�
  • Unit II: Wrangle (3 weeks)
  • Unit III: Program (2 weeks)
  • Unit IV: Model (2 weeks)
  • Unit V: Communicate (2 weeks)