Statistics Prerequisite

2025 Fall
#22786

Introduction to Probability and Statistics

Aug 27, 2025 - Dec 12, 2025
12:00 am

Instruction Mode: In-Person Instruction

No Open Seats
STAT 20 - LEC 001 Introduction to Probability and Statistics more detail
For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.
2025 Fall
#27075

Probability for Data Science

Instruction Mode: In-Person Instruction

No Open Seats
STAT C140 - VOL 999V 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
#27563

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
11:00 am - 12:59 pm

Instruction Mode: In-Person Instruction

No Open Seats
STAT 135 - LAB 102 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
#23277

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
03:00 pm - 04:59 pm

Instruction Mode: In-Person Instruction

No Open Seats
STAT 135 - LAB 104 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
#23276

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
01:00 pm - 02:59 pm

Instruction Mode: In-Person Instruction

No Open Seats
STAT 135 - LAB 103 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
#22872

Concepts of Statistics

Aug 27, 2025 - Dec 12, 2025
Tu
09:00 am - 10:59 am

Instruction Mode: In-Person Instruction

No Open Seats
STAT 135 - LAB 101 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
#22871

Concepts of Statistics

Adam R Lucas
Aug 27, 2025 - Dec 12, 2025
Mo, We, Fr
09:00 am - 09:59 am

Instruction Mode: In-Person Instruction

Open Seats

3 Unreserved Seats

STAT 135 - LEC 001 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
#24650

Statistical Methods for Data Science

Aug 27, 2025 - Dec 12, 2025
Tu, Th
02:00 pm - 03:00 pm

Instruction Mode: In-Person Instruction

No Open Seats
STAT C131A - LAB 102 Statistical Methods for Data Science more detail
This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.
2025 Fall
#24649

Statistical Methods for Data Science

Aug 27, 2025 - Dec 12, 2025
Tu, Th
10:00 am - 11:00 am

Instruction Mode: In-Person Instruction

No Open Seats
STAT C131A - LAB 101 Statistical Methods for Data Science more detail
This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.
2025 Fall
#24648

Statistical Methods for Data Science

Shobhana Murali Stoyanov
Aug 27, 2025 - Dec 12, 2025
Tu, Th
08:00 am - 09:29 am

Instruction Mode: In-Person Instruction

No Open Seats
STAT C131A - LEC 001 Statistical Methods for Data Science more detail
This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.