2 courses with the subject DATA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DATA 251Data and Context Data matter! But how do we build datasets? How do the data from experiments and
observational research differ? How are data from different studies aggregated to perform meta-analysis? What choices do we make to group, merge, collapse, link, and represent abstract concepts with data? How do we cope with missing data? What information do we gain or lose by making these choices? How do we answer questions once we’ve constructed and cleaned our data? How do these choices alter the stories we tell with the data that we’ve collected? This course will explore these questions with real-world applications from a variety of disciplines. Our focus will be on the ethics and consequences of the choices we make when working with real-world data sets. offered annually)
DATA 101, DATA 127, and DATA 227 with a grade of C- or higher, or permission of the instructor. (Staff,
DATA 353Data Analytics Capstone The capstone course for the Data Analytics minor centers on client-focused
projects. Students will work collaboratively with a “client” to provide an analysis to meet their specific needs. Students begin with a thematic question or problem that can be addressed with a large data set—generally larger than 1,000 records. Students may assemble a dataset as part of the project or use existing data. The question will be drawn from the student’s major academic focus and involve visualization, analytics, and modeling. Each student will produce a web-based Shiny application that will permit users to interact with the underlying data to address the thematic question/problem posed. Class meetings will be structured as workshops to support the student through each stage of the process of developing their question, assembling, cleaning, and linking data, developing a concept for the dashboard, and developing/testing the needed code. Language acquisition will focus on the Shiny package in R. Workshops will encourage collaborative and self-directed problem solving and provide practice giving and receiving peer feedback. At the end of the semester, students will host their Shiny dashboard and a process blog that will describe the student’s development process and workflow. This blog will describe the question/prob- lem and provide context for it. Students will then report on their workflow, highlighting problems encountered and how they solved them. Completed dashboard and blog posts will be hosted publicly so that students can link their work to their resume as a portfolio of practice. Requires DATA 251 with a grade of C- or higher, or permission of the instructor. (Staff, offered annually) HWS.EDU/CATALOGUE 168 2023 - 2024 CATALOGUE
