2023 Fall
DATA C140 001 - LEC 001
Formerly Statistics 140
Probability for Data Science
Ani Adhikari, Alexander Strang
Class #:25241
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Data Science Undergraduate Studies
Current Enrollment
Total Open Seats:
2
Enrolled: 298
Waitlisted: 0
Capacity: 300
Waitlist Max: 0
No Reserved Seats
Hours & Workload
3 hours of instructor presentation of course materials per week, 7 to 8 hours of outside work hours per week, 0 to 1 hours of extra meetings for the review or elaboration of course materials per week, and 2 hours of the exchange of opinions or questions on course material per week.
Final Exam
FRI, DECEMBER 15TH
07:00 pm - 10:00 pm
Dwinelle 155
Dwinelle 145
Other classes by Ani Adhikari
Course Catalog Description
An introduction to probability, emphasizing the combined use of mathematics and programming. Discrete and continuous families of distributions. Bounds and approximations. Transforms and convergence. Markov chains and Markov Chain Monte Carlo. Dependence, conditioning, Bayesian methods. Maximum likelihood, least squares prediction, the multivariate normal, and multiple regression. Random permutations, symmetry, and order statistics. Use of numerical computation, graphics, simulation, and computer algebra.
Class Notes
*Prerequisites for this course are ENFORCED.
*Course will not allow for time conflicts nor will it accommodate final exam conflicts.
*Class will likely have two out-of-class midterm exams at TBD dates.
*If you completed an approved alternate UC Berkeley prerequ.. show more
*Course will not allow for time conflicts nor will it accommodate final exam conflicts.
*Class will likely have two out-of-class midterm exams at TBD dates.
*If you completed an approved alternate UC Berkeley prerequ.. show more
*Prerequisites for this course are ENFORCED.
*Course will not allow for time conflicts nor will it accommodate final exam conflicts.
*Class will likely have two out-of-class midterm exams at TBD dates.
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit a request to clear requisites for Data C140. See our Enrollment FAQ for details: https://docs.google.com/document/d/1yHo13u6nN0EjVJq5EW0BswuAQPeEC_Oeb8Aprpqsk7k/edit?usp=sharing
*This class uses 999 sections. In addition to the lecture, you must enroll in the DIS 999 to enroll in the course. Selection and assignment into the actual sections happen outside of CalCentral. Instructors will provide more information during the first lecture. show less
*Course will not allow for time conflicts nor will it accommodate final exam conflicts.
*Class will likely have two out-of-class midterm exams at TBD dates.
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit a request to clear requisites for Data C140. See our Enrollment FAQ for details: https://docs.google.com/document/d/1yHo13u6nN0EjVJq5EW0BswuAQPeEC_Oeb8Aprpqsk7k/edit?usp=sharing
*This class uses 999 sections. In addition to the lecture, you must enroll in the DIS 999 to enroll in the course. Selection and assignment into the actual sections happen outside of CalCentral. Instructors will provide more information during the first lecture. show less
Rules & Requirements
Requisites
- DATA/COMPSCI/INFO/STAT C8, or both STAT 20 and one of COMPSCI 61A or COMPSCI/DATA C88C with C- or better, or Pass; and one year of calculus at the level of MATH 1A-1B or higher, with C- or better, or Pass. Corequisite: MATH 54, MATH 56, EECS 16B, MATH 110 or equivalent linear algebra (C- or better, or Pass, required if completed prior to enrollment in Data/Stat C140).
Credit Restrictions
Students will receive no credit for STAT C140 after completing STAT 134, or EECS 126. A deficient grade in STAT C140 may be removed by taking STAT 134.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials