CS 361 - Prob & Stat for Computer Sci

Fall 2022

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Prob & Stat for Computer SciCS361ADA72361DIS00900 - 0950 M  1105 Siebel Center for Comp Sci Zewei Long
Hongye Liu
Prob & Stat for Computer SciCS361ADB66306DIS01000 - 1050 M  1105 Siebel Center for Comp Sci Aditya Karan
Hongye Liu
Prob & Stat for Computer SciCS361ADC66307DIS01100 - 1150 M  1105 Siebel Center for Comp Sci Aditya Karan
Hongye Liu
Prob & Stat for Computer SciCS361ADD66303DIS01200 - 1250 M  1105 Siebel Center for Comp Sci Weijiang Li
Hongye Liu
Prob & Stat for Computer SciCS361ADE66304DIS01300 - 1350 M  1105 Siebel Center for Comp Sci Lilac Lai
Hongye Liu
Prob & Stat for Computer SciCS361ADF66305DIS01400 - 1450 M  1105 Siebel Center for Comp Sci Tony Xuetao Tan
Hongye Liu
Prob & Stat for Computer SciCS361ADG76052DIS01500 - 1550 M  1105 Siebel Center for Comp Sci Shuhong Zheng
Hongye Liu
Prob & Stat for Computer SciCS361ADH76054DIS01600 - 1650 M  1105 Siebel Center for Comp Sci Ikhyun Cho
Hongye Liu
Prob & Stat for Computer SciCS361AL166298LEC31100 - 1215 T R  1002 Electrical & Computer Eng Bldg Hongye Liu
Prob & Stat for Computer SciSTAT361ADA72362DIS00900 - 0950 M  1105 Siebel Center for Comp Sci Zewei Long
Hongye Liu
Prob & Stat for Computer SciSTAT361ADB66311DIS01000 - 1050 M  1105 Siebel Center for Comp Sci Aditya Karan
Hongye Liu
Prob & Stat for Computer SciSTAT361ADC66312DIS01100 - 1150 M  1105 Siebel Center for Comp Sci Aditya Karan
Hongye Liu
Prob & Stat for Computer SciSTAT361ADD66308DIS01200 - 1250 M  1105 Siebel Center for Comp Sci Weijiang Li
Hongye Liu
Prob & Stat for Computer SciSTAT361ADE66309DIS01300 - 1350 M  1105 Siebel Center for Comp Sci Lilac Lai
Hongye Liu
Prob & Stat for Computer SciSTAT361ADF66310DIS01400 - 1450 M  1105 Siebel Center for Comp Sci Tony Xuetao Tan
Hongye Liu
Prob & Stat for Computer SciSTAT361ADG76053DIS01500 - 1550 M  1105 Siebel Center for Comp Sci Shuhong Zheng
Hongye Liu
Prob & Stat for Computer SciSTAT361ADH76055DIS01600 - 1650 M  1105 Siebel Center for Comp Sci Ikhyun Cho
Hongye Liu
Prob & Stat for Computer SciSTAT361AL166299LEC31100 - 1215 T R  1002 Electrical & Computer Eng Bldg Hongye Liu

Official Description

Introduction to probability theory and statistics with applications to computer science. Topics include: visualizing datasets, summarizing data, basic descriptive statistics, conditional probability, independence, Bayes theorem, random variables, joint and conditional distributions, expectation, variance and covariance, central limit theorem. Markov inequality, Chebyshev inequality, law of large numbers, Markov chains, simulation, the PageRank algorithm, populations and sampling, sample mean, standard error, maximum likelihood estimation, Bayes estimation, hypothesis testing, confidence intervals, linear regression, principal component analysis, classification, and decision trees. Course Information: Same as STAT 361. Credit is not given for both CS 361 and ECE 313. Prerequisite: MATH 220 or MATH 221; credit or concurrent registration in one of MATH 225, MATH 257, MATH 415, MATH 416 or ASRM 406. For majors only.

Course Director

Text(s)

Forsyth, D. A. "Probability and Statistics for Computer Science," Springer (2018)

Learning Goals

Visualize and summarize data and reason about outliers and relationships (1), (3)

Apply the principles of probability to analyze and simulate random events (1)

Use inference to fit statistical models to data and evaluate how good the fit is (1), (3)

Apply machine learning tools to dimensionality reduction, classification, clustering, regression and hidden Markov model problems (1), (2), (6)

Topic List

visualizing datasets, summarizing data, basic descriptive statistics, conditional probability, independence, Bayes theorem, random variables, joint and conditional distributions, expectation, variance and covariance, central limit theorem. Markov inequality, Chebyshev inequality, law of large numbers, Markov chains, simulation, the PageRank algorithm, populations and sampling, sample mean, standard error, maximum likelihood estimation, Bayes estimation, hypothesis testing, confidence intervals, linear regression, principal component analysis, classification, decision trees, clustering and Markov chains

Last updated

2/7/2019by David Varodayan