Probability

2025 Fall
#29293
EECS 126 104D - DIS 104D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Aug 27, 2025 - Dec 12, 2025
Fr
08:00 am - 08:59 am
Lewis 9
Class #:29293
Units:4

Instruction Mode: In-Person Instruction

Open Seats

57 Unreserved Seats

EECS 126 - DIS 104D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
2025 Fall
#29292
EECS 126 103D - DIS 103D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Aug 27, 2025 - Dec 12, 2025
We
10:00 am - 10:59 am
Cory 241
Class #:29292
Units:4

Instruction Mode: In-Person Instruction

Open Seats

54 Unreserved Seats

EECS 126 - DIS 103D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
2025 Fall
#29286
EECS 126 001 - LEC 001 offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Preeya Khanna
Aug 27, 2025 - Dec 12, 2025
Tu, Th
12:30 pm - 01:59 pm
Hearst Mining 390
Class #:29286
Units:4

Instruction Mode: In-Person Instruction

Open Seats

EECS 126 - LEC 001 Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
2025 Fall
#24681
DATA C140 001 - LEC 001 offered through Data Science Undergraduate Studies

Probability for Data Science

Alexander Strang
Aug 27, 2025 - Dec 12, 2025
Tu, Th
03:30 pm - 04:59 pm
Dwinelle 155
Class #:24681
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - LEC 001 Probability for Data Science more detail
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.
2025 Summer Session C 8 weeks, June 23 - August 15
#12705
STAT 134 104 - DIS 104 offered through Statistics

Concepts of Probability

Jun 23, 2025 - Aug 15, 2025
Mo, Tu, We, Th
04:00 pm - 04:59 pm
Evans 330
Class #:12705
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
STAT 134 - DIS 104 Concepts of Probability more detail
An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.
How to apply
2025 Summer Session C 8 weeks, June 23 - August 15
#12323
STAT 134 103 - DIS 103 offered through Statistics

Concepts of Probability

Jun 23, 2025 - Aug 15, 2025
Mo, Tu, We, Th
03:00 pm - 03:59 pm
Evans 330
Class #:12323
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
STAT 134 - DIS 103 Concepts of Probability more detail
An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.
How to apply
2025 Summer Session C 8 weeks, June 23 - August 15
#12322
STAT 134 102 - DIS 102 offered through Statistics

Concepts of Probability

Jun 23, 2025 - Aug 15, 2025
Mo, Tu, We, Th
03:00 pm - 03:59 pm
Evans 332
Class #:12322
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
STAT 134 - DIS 102 Concepts of Probability more detail
An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.
How to apply
2025 Summer Session C 8 weeks, June 23 - August 15
#12321
STAT 134 101 - DIS 101 offered through Statistics

Concepts of Probability

Jun 23, 2025 - Aug 15, 2025
Mo, Tu, We, Th
02:00 pm - 02:59 pm
Evans 332
Class #:12321
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
STAT 134 - DIS 101 Concepts of Probability more detail
An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.
How to apply
2025 Summer Session C 8 weeks, June 23 - August 15
#12320
STAT 134 001 - LEC 001 offered through Statistics

Concepts of Probability

Jun 23, 2025 - Aug 15, 2025
Mo, Tu, We, Th
12:30 pm - 01:59 pm
North Gate 105
Class #:12320
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
STAT 134 - LEC 001 Concepts of Probability more detail
An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.
How to apply

INDENG 172 (2015-01-13 - 2015-01-13)

This is an introductory probability course for students in engineering. It focuses mostly on random variables and their applications. Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, computer science, and others. Note: This course is a statistics course and cannot be used to fulfill any engineering unit or elective requirements.
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