Quantitative Sciences Minor
"I personally think there's going to be a greater demand in 10 years for liberal arts majors than there were for programming majors and maybe even engineering, because when the data is all being spit out for you, . . . you need a different perspective in order to have a different view of the data. . . . [S]omeone who is more of a freer thinker." -Mark Cuban, American Businessman & investor, owner of the Dallas Mavericks
Launching in Fall 2018, the Quantitative Sciences minor offers Emory students an option to establish or enhance a statistical and computational skillset while pursuing another major program, and without the curricular commitment of a full Quantitative Sciences B.S. degree.
The Quantitative Sciences minor is a program that establishes or enhances students’ quantitative skillsets without the curricular commitment of a full Quantitative Sciences Bachelor of Science. It is suitable for students interested in establishing a statistical and computational skillset while pursuing another major program. This minor is useful for those who intend on pursuing a career in fields that utilize data and data science techniques, as well as those who desire a basic facility with data without the mathematical rigor of QTM's major programs.
The minor consists of 8 courses totalling 22+ credit hours. QTM 100 is the foundational course for the minor in Quantitative Sciences.
Beyond the obvious credit hour differences (the minor requires 22+ credit hours while the QSS major requires 50+ credit hours) and the degree type differences (minor degree vs. B.S. degree), the Quantitative Sciences minor consists of a somewhat different set of courses and concepts.
The minor is built around the foundational course QTM 100: Introduction to Statistical Inference. The proceeding courses teach students how to think critically about data, the principles of quantitative research, how to apply statistical concepts to a broader field of statistical analysis, critical skills and concepts in computer programming and inference using Python, and computing skills in R. Students also choose two upper-level electives, where they will apply their foundational skill set.
The minor is intended for students who are interested in learning how to work with data, but are not interested in pursuing a full major and/or are not comfortable with the level of mathematical rigor required for QTM's other major programs.
Minor students can take any 300- or 400- level seminar / lecture style QTM elective that do not have QSS major core courses as prerequisites. What does this mean exactly? Any QTM elective course that lists QTM 120/210/220 (these are QSS major courses) as prerequisites is not avilable to QSS minors.
We offer a number of QTM upper-level electives that QSS minors can take. These include, but are not limited to, Technical Writing, Game Theory, Practical Approaches to Data Science with Text, Introductory Network Analysis, Fundamentals of Cartography and GIS, and Big/Small Data & Visualization, and Social Choice & Elections.
I see that QTM offers two data science computing courses: QTM 250 (Foundational Data Science Computing) and QTM 350 (Data Science Computing). Are these interchangeable?
No. QTM 250: Foundational Data Science Computing is a required course in the QSS minor. QTM 350: Data Science Computing is a more advanced course and a QSS major elective. QTM 350 is not an elective option in the QSS minor.
QTM oversees the adminsitration of the minor. You can declare the minor (starting Fall 2018) here after which you will receive an email from QTM with further instructions.