Stanford Root

Schedule

Stanford Root

Schedule

OIT 276

Data and Decisions - Accelerated (Flipped Classroom)

UNITS:3
GRADING:GSB Letter Graded
LEVEL:Graduate
GER:—

Accelerated Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a more lab-based classroom approach. Traditional lecture content will be learned through online videos, simulations, and exercises, while time spent in the classroom will be discussions, problem solving, or computer lab sessions. Content covered includes sampling techniques, hypothesis testing, t-tests, linear regression, and prediction models. The group regression project is a key component of the course, and all students will learn the statistical software package R. The accelerated course is designed for students with strong quantitative backgrounds. Students taking this course need to be comfortable with mathematical notation, algebra, and basic probability. Students without quantitative backgrounds should consider enrolling in the base version of the course.

Syllabus for selected term:
View Winter 2027 Syllabus

Sections

1 Term
Case Study 1Open
ID: 27264
0 / 50 enrolled
DAYS:Monday, Thursday
TIME:8:15 AM – 9:35 AM
LOCATION:Not Applicable
INSTRUCTOR:
Spiess, Jann
3units
Case Study 2Open
ID: 27265
0 / 50 enrolled
DAYS:Monday, Thursday
TIME:10 AM – 11:20 AM
LOCATION:Not Applicable
INSTRUCTOR:
Spiess, Jann
3units

OIT 276: Data and Decisions - Accelerated (Flipped Classroom)

3 units · GSB Letter Graded

Accelerated Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a more lab-based classroom approach. Traditional lecture content will be learned through online videos, simulations, and exercises, while time spent in the classroom will be discussions, problem solving, or computer lab sessions. Content covered includes sampling techniques, hypothesis testing, t-tests, linear regression, and prediction models. The group regression project is a key component of the course, and all students will learn the statistical software package R. The accelerated course is designed for students with strong quantitative backgrounds. Students taking this course need to be comfortable with mathematical notation, algebra, and basic probability. Students without quantitative backgrounds should consider enrolling in the base version of the course.

Offered in Winter 2027 at Stanford University.

Winter 2027 sections

  • Case Study — Monday Thursday 10:00 AM – 11:20 AM — Spiess, Jann (Graduate)
  • Case Study — Monday Thursday 8:15 AM – 9:35 AM — Spiess, Jann (Graduate)

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