Statistics Prerequisite

2025 Fall
#24911
DATA C140 101 - DIS 101 offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
We
09:00 am - 09:59 am
Evans 330
Class #:24911
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - DIS 101 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 Fall
#33482
STAT 135 106 - LAB 106 offered through Statistics

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
04:00 pm - 05:59 pm
Evans 330
Class #:33482
Units:4

Instruction Mode: In-Person Instruction

Open Seats

22 Unreserved Seats

STAT 135 - LAB 106 Concepts of Statistics more detail
A comprehensive survey course in statistical theory and methodology. Topics include descriptive statistics, maximum likelihood estimation, non-parametric methods, introduction to optimality, goodness-of-fit tests, analysis of variance, bootstrap and computer-intensive methods and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.
2025 Fall
#33481
STAT 135 105 - LAB 105 offered through Statistics

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
02:00 pm - 03:59 pm
Evans 330
Class #:33481
Units:4

Instruction Mode: In-Person Instruction

Open Seats

5 Unreserved Seats

STAT 135 - LAB 105 Concepts of Statistics more detail
A comprehensive survey course in statistical theory and methodology. Topics include descriptive statistics, maximum likelihood estimation, non-parametric methods, introduction to optimality, goodness-of-fit tests, analysis of variance, bootstrap and computer-intensive methods and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.
2025 Fall
#26529
DATA C140 114S - SUP 114S offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
Fr
01:00 pm - 01:59 pm
Stanley 106
Class #:26529
Units:4

Instruction Mode: In-Person Instruction

Open Seats

1 Unreserved Seats

DATA C140 - SUP 114S 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 Fall
#26326
DATA C140 113S - SUP 113S offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
Fr
12:00 pm - 12:59 pm
Stanley 106
Class #:26326
Units:4

Instruction Mode: In-Person Instruction

Open Seats

1 Unreserved Seats

DATA C140 - SUP 113S 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 Fall
#26325
DATA C140 112S - SUP 112S offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
Fr
11:00 am - 11:59 am
Valley Life Sciences 2040
Class #:26325
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - SUP 112S 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 Fall
#24919
DATA C140 109 - DIS 109 offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
We
03:00 pm - 03:59 pm
Evans 330
Class #:24919
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - DIS 109 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 Fall
#24918
DATA C140 108 - DIS 108 offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
We
02:00 pm - 02:59 pm
Evans 330
Class #:24918
Units:4

Instruction Mode: In-Person Instruction

Open Seats

1 Unreserved Seats

DATA C140 - DIS 108 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 Fall
#24916
DATA C140 106 - DIS 106 offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
We
01:00 pm - 01:59 pm
Evans 330
Class #:24916
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - DIS 106 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 Fall
#24915
DATA C140 105 - DIS 105 offered through Data Science Undergraduate Studies

Probability for Data Science

Aug 27, 2025 - Dec 12, 2025
We
12:00 pm - 12:59 pm
Evans 332
Class #:24915
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - DIS 105 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.
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