STOR Courses

Here is information about STOR class enrollment for summer I 2024. Classes with no meeting time listed are not shown. Feel free to contact me with any questions/comments/issues. I am happy to add any departments that are missing from these listings, just reach out to ask!

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Data also available for: COMP, AMST, COMM, MATH, STOR

Data last updated: 2024-05-15 15:57:23.404010

Class Number	Class	Meeting Time	Instructor	Room	Unreserved Enrollment	Reserved Enrollment	Total Enrollment	Wait List
1323	STOR 113 - 001 Decision Models for Business and Economics	MoTuWeThFr 11:30AM - 1:00PM	Dilay Ozkan	Hanes Hall-Rm 0107	11/30	Seats filled	11/30	0/999
Description: Prerequisite, MATH 110. An introduction to multivariable quantitative models in economics. Mathematical techniques for formulating and solving optimization and equilibrium problems will be developed, including elementary models under uncertainty. 3 units.
1325	STOR 120 - 001 Foundations of Statistics and Data Science	MoTuTh 9:45AM - 11:45AM	Jeff McLean	Dey Hall-Rm 0307	9/30	Seats filled	9/30	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 4 units.
1326	STOR 120 - 002 Foundations of Statistics and Data Science	MoTuTh 1:15PM - 3:15PM	Jeff McLean	Hanes Hall-Rm 0120	12/30	Seats filled	12/30	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 4 units.
1336	STOR 120 - 400 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Ishmael Benjamin Torres Aguilar	Hanes Hall-Rm 0107	4/5	Seats filled	4/5	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 0 units.
1335	STOR 120 - 401 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Can Er	Dey Hall-Rm 0208	5/7	Seats filled	5/7	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 0 units.
1334	STOR 120 - 402 Foundations of Statistics and Data Science	WeFr 1:15PM - 2:10PM	Ishmael Benjamin Torres Aguilar	Hanes Hall-Rm 0107	Seats filled	Seats filled	6/6	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 0 units.
1333	STOR 120 - 403 Foundations of Statistics and Data Science	WeFr 1:15PM - 2:10PM	Can Er	Dey Hall-Rm 0405	6/13	Seats filled	6/13	0/999
Description: The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. 0 units.
1327	STOR 155 - 001 Introduction to Data Models and Inference	MoTuWeThFr 9:45AM - 11:15AM	Oluremi Abayomi	Hanes Hall-Rm 0120	Seats filled	Seats filled	25/25	0/999
Description: Prerequisite, MATH 110. Data analysis; correlation and regression; sampling and experimental design; basic probability (random variables, expected values, normal and binomial distributions); hypothesis testing and confidence intervals for means, proportions, and regression parameters; use of spreadsheet software. 3 units.
1328	STOR 155 - 002 Introduction to Data Models and Inference	MoTuWeThFr 11:30AM - 1:00PM	Panagiotis Andreou	Hanes Hall-Rm 0130	9/30	Seats filled	9/30	0/999
Description: Prerequisite, MATH 110. Data analysis; correlation and regression; sampling and experimental design; basic probability (random variables, expected values, normal and binomial distributions); hypothesis testing and confidence intervals for means, proportions, and regression parameters; use of spreadsheet software. 3 units.
1329	STOR 155 - 003 Introduction to Data Models and Inference	MoTuWeThFr 1:15PM - 2:45PM	WILLIAM LASSITER	Hanes Hall-Rm 0130	6/30	Seats filled	6/30	0/999
Description: Prerequisite, MATH 110. Data analysis; correlation and regression; sampling and experimental design; basic probability (random variables, expected values, normal and binomial distributions); hypothesis testing and confidence intervals for means, proportions, and regression parameters; use of spreadsheet software. 3 units.
2167	STOR 320 - 001 Introduction to Data Science	MoTuWeTh 12:45PM - 2:45PM	Oluremi Abayomi	Dey Hall-Rm 0206	25/45	Seats filled	25/45	0/999
Description: Prerequisite, STOR 120 or 155. Development of basic skill set for data analysis from obtaining data to data carpentry, exploration, modeling, and communication. Topics covered include regression, clustering, classification, algorithmic thinking, and non-standard data objects (networks and text data). Students may not receive credit for both STOR 320 and STOR 520. 4 units.
2168	STOR 320 - 400 Introduction to Data Science	Fr 12:45PM - 2:45PM	Dilshad Imon	Hanes Hall-Rm 0112	10/15	Seats filled	10/15	0/999
Description: Prerequisite, STOR 120 or 155. Development of basic skill set for data analysis from obtaining data to data carpentry, exploration, modeling, and communication. Topics covered include regression, clustering, classification, algorithmic thinking, and non-standard data objects (networks and text data). Students may not receive credit for both STOR 320 and STOR 520. 0 units.
2169	STOR 320 - 401 Introduction to Data Science	Fr 12:45PM - 2:45PM	Coleman Ferrell	Dey Hall-Rm 0302	Seats filled	Seats filled	15/15	0/999
Description: Prerequisite, STOR 120 or 155. Development of basic skill set for data analysis from obtaining data to data carpentry, exploration, modeling, and communication. Topics covered include regression, clustering, classification, algorithmic thinking, and non-standard data objects (networks and text data). Students may not receive credit for both STOR 320 and STOR 520. 0 units.
1331	STOR 435 - 001 Introduction to Probability	MoTuWeThFr 9:45AM - 11:15AM	CHUANSHU JI	Hanes Hall-Rm 0125	10/50	Seats filled	10/50	0/999
Description: Prerequisites, MATH/STOR 235 or MATH 233; and STOR 215 or MATH 381 or COMP 283. Introduction to mathematical theory of probability covering random variables; moments; binomial, Poisson, normal and related distributions; generating functions; sums and sequences of random variables; and statistical applications. Students may not receive credit for both STOR 435 and STOR 535. 3 units.
1332	STOR 435 - 002 Introduction to Probability	MoTuWeThFr 11:30AM - 1:00PM	CHUANSHU JI	Hanes Hall-Rm 0125	14/50	Seats filled	14/50	0/999
Description: Prerequisites, MATH/STOR 235 or MATH 233; and STOR 215 or MATH 381 or COMP 283. Introduction to mathematical theory of probability covering random variables; moments; binomial, Poisson, normal and related distributions; generating functions; sums and sequences of random variables; and statistical applications. Students may not receive credit for both STOR 435 and STOR 535. 3 units.