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STAT 359-0 : Topics in Statistics: Foundations of Data Science with R (Topics in Statistics: Foundations of Data Science with R)

Description

IMPORTANT for Northwestern Students: This course cannot be used to fulfill requirements for a Data Science major or Data Science minor. Students may not substitute this STAT 359 for STAT 301-1, STAT 301-2, STAT 301-3, STAT 303-1, STAT 303-2, STAT 303-3, or STAT 302 nor can it be used for an elective for the Data Science major/minor.

This course is intended for students who want to learn data exploration and modeling in R but do not intend to pursue a data science major or minor or take the Data Science sequence. The course builds a basic foundation of analytical skills and knowledge for conducting data science in R. While many data science problems will require knowledge of multiple coding languages and technologies, this course chooses to utilize R and RStudio to conduct data science. Students will develop skills to effectively manage, manipulate, and analyze data in R the first 4 weeks. Students will then be introduced to machine learning and will develop skills, tools, and strategies for modeling and understanding complex data the next 4 weeks. These skills will be developed through lab-based learning (1 lab per week). The final week will focus on putting all these skills together into a final project.

The class will be remote asynchronous instruction, meaning this course is conducted completely online and geared toward independent learners who have prior coding experience. A typical lesson will include a textbook reading, a sequence of instructional videos to watch, and a lab to complete. While the course material will be delivered asynchronously, students will be required to meet weekly deadlines throughout the 10 weeks of the course. There will be 1 lab due each of the first 8 weeks and a final project due the last week. The course will have a discussion board where students are encouraged to engage with each other by both asking and answering questions. The instructor will also be actively engaged with the students through the course discussion board and will hold virtual office hours each week.

Prerequisites/Registration Requirements: STAT 201-0 or COMP_SCI 110-0 or STAT 202-0 or consent of the instructor. IMPORTANT for Northwestern Students: This course cannot be used to fulfill requirements for a Data Science major or Data Science minor. Students may not substitute this STAT 359 for STAT 301-1, STAT 301-2, STAT 301-3, STAT 303-1, STAT 303-2, STAT 303-3, or STAT 302 nor can it be used for an elective for the Data Science major/minor. Students should consult the Undergraduate Catalog and/or the department to confirm if the course they want to register for will fulfill their desired requirement.

Teaching Method: The class will be remote asynchronous instruction, meaning this course is conducted completely online. A typical lesson will include a textbook reading, a sequence of instructional videos to watch, and a lab to complete. While the course material will be delivered asynchronously, students will be required to meet weekly deadlines throughout the 10 weeks of the course. There will be 1 lab due each of the first 8 weeks and a final project due the last week.

Evaluation Method: Students will be evaluated through (1) reading notes, (2) labs, (3) final project

Required Class Materials: (1) R for Data Science by Hadley Wickham & Garrett Grolemund -- Free online version: http://r4ds.had.co.nz/ (2) Tidy Modeling with R -- Free online version: https://www.tmwr.org/ (3) Free statistical software R (https://cran.rstudio.com/) (4) Free integrated development environment software RStudio (https://www.rstudio.com/). Think of R as the car engine needed to power and run everything while RStudio is the steering wheel/dashboard that we use to run and control the car.