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Data Analytics

Data Analytics applies statistical and computational methods to specific fields of inquiry and decision-making.

The Bachelor of Arts with a major in Data Analytics prepares students for a range of careers in which data must be manipulated, contextualized, and applied to the problems of today. The program trains students to work with the ever-broadening expanse of data that is rapidly transforming industry, business, the public sphere, and many fields of research.

The degree coursework combines a core of flexible analytical skills with in-depth advanced knowledge in transdisciplinary subjects in natural science, social science, humanities, and/or sport. This combination provides a solid 4-year liberal education along with early development of practical skills widely sought by employers from interns and new college graduates.

Prerequisites

The BA in Data Analytics requires prior completion of an introductory statistics course and a sufficient background in high-school mathematics to enroll in pre-calculus.

Degree Core

The 19-credit hour core of the degree comprises 6 technical courses taken in the first two years. These focus on topics of fundamental and immediate use in analytics and its applications.

Concentrations

Along with the degree core above, students choose an 18-19-credit hour concentration in one of several fields. Each concentration includes 6 courses that can be taken across 3 or 4 years.

Currently, the following concentrations are offered:

  • Geospatial Analytics
  • Bioinformatics
  • Sport Analytics
  • Social Data

Additional concentrations in the social sciences and humanities are under development.

Suggested Semester-by-Semester Schedules

These schedules are for entering students who have not yet taken introductory statistics. Students who have already received credit for introductory statistics (STA 261 or STA 301) should take STA 363 in the fall semester of Year 1, followed by STA/POL 308 in the spring semester of Year 1 and STA/POL 309 in the fall semester of Year 2. GMP refers to Global 兔子先生 Plan courses.

Concentration in Bioformatics

Year 1

Fall Semester

  • MTH 133 (4 hr)
  • STA 261 (4 hr) [STA 301 is recommended if the student already has credit for Calculus 1.]
  • Electives/GMP (7-9 hr)

Spring Semester

  • STA 363 (3 hr)
  • BIO/MBI 116 (4 hr)
  • Electives/GMP (8-9 hr)

Year 2

Fall Semester

  • STA/POL 308 (3 hr)
  • ENG/STC 285 (3 hr)
  • BIO/MBI 256 (3 hr)
  • Electives/GMP (6-7 hr)

Spring Semester

  • STA/POL 309 (3 hr)
  • PHL/HST/GIC 286 (3 hr)
  • BIO or MBI or CHM elective (3-4 hr)
  • Electives/GMP (6-7 hr)

Year 3

Fall Semester

  • BIO/MBI/CHM/CSE 466 (3 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • BIO/MBI 485 (3 hr)
  • Electives/GMP (12-13 hr)

Year 4

Fall Semester

  • BIO or MBI or CHM elective (3-4 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • Electives/GMP (15-16 hr)

Concentration in Geospatial Analytics

Year 1

Fall Semester

  • MTH 133 (4 hr)
  • STA 261 (4 hr) [STA 301 is recommended if the student already has credit for Calculus 1.]
  • GEO or GLG elective (3-4 hr)
  • Electives/GMP (4-5 hr)

Spring Semester

  • STA 363 (3 hr)
  • GEO 242(3 hr)
  • Electives/GMP (9-10 hr)

Year 2

Fall Semester

  • STA/POL 308 (3 hr)
  • ENG/STC 285 (3 hr)
  • GEO 441 (3 hr)
  • Electives/GMP (6-7 hr)

Spring Semester

  • STA/POL 309 (3 hr)
  • PHL/HST/GIC 286 (3 hr)
  • GEO 442 (3 hr)
  • Electives/GMP (6-7 hr)

Year 3

Fall Semester

  • GEO 448 (3 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • Electives/GMP (15-16 hr)

Year 4

Fall Semester

  • GEO elective (3-4 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • Electives/GMP (15-16 hr)

Concentration in Sport Analytics

Year 1

Fall Semester

  • MTH 133 (4 hr)
  • STA 261 (4 hr) [STA 301 is recommended if the student already has credit for Calculus 1.]
  • Electives/GMP (7-9 hr)

Spring Semester

  • STA 363 (3 hr)
  • KNH 273 (3 hr)
  • Electives/GMP (8-9 hr)

Year 2

Fall Semester

  • STA/POL 308 (3 hr)
  • ENG/STC 285 (3 hr)
  • KNH 275 (3 hr)
  • Electives/GMP (6-7 hr)

Spring Semester

  • STA/POL 309 (3 hr)
  • PHL/HST/GIC 286 (3 hr)
  • KNH 313 (3 hr)
  • Electives/GMP (6-7 hr)

Year 3

Fall Semester

  • BIO/MBI/CHM/CSE 466 (3 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • KNH 416 (3 hr)
  • Electives/GMP (12-13 hr)

Year 4

Fall Semester

  • KNH 418 (3 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • Electives/GMP (15-16 hr)

Concentration in Social Data

Year 1

Fall Semester

  • MTH 133 (4 hr)
  • STA 261 (4 hr)
  • GTY, POL, or SOC intro elective (3 hr)
  • Electives/GMP (4-6 hr)

Spring Semester

  • STA 363 (3 hr)
  • Electives/GMP (12-13 hr)

Year 2

Fall Semester

  • STA 308 (3 hr)
  • ENG/STC 285 (3 hr)
  • GTY, POL, or SOC advanced elective (3 hr)
  • Electives/GMP (6-7 hr)

Spring Semester

  • STA 309 (3 hr)
  • PHL/HST/GIC 286 (3 hr)
  • GTY, POL, or SOC data elective (3-4 hr)
  • Electives/GMP (6-7 hr)

Year 3

Fall Semester

  • Electives/GMP (15-16 hr)

Spring Semester

  • GTY, POL, or SOC data elective (3 hr)
  • Electives/GMP (12-13 hr)

Year 4

Fall Semester

  • GTY, POL, or SOC data elective (3-4 hr)
  • Electives/GMP (12-13 hr)

Spring Semester

  • GTY, POL, or SOC advanced elective (3 hr)
  • Electives/GMP (12-13 hr)

Data Analytics

Lisa Werwinski, Statistics Chief Departmental Advisor
334F Upham Hall
Oxford, OH 45056
513-529-3406