STOR Courses

Here is information about STOR class enrollment for summer I 2023. Classes with no meeting time listed are not shown. Feel free to contact me with any questions/comments/issues.

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

Data last updated: 2023-07-04 20:29:53.312562

Class Number	Class	Meeting Time	Instructor	Room	Unreserved Enrollment	Reserved Enrollment
1733	STOR 113 - 001 Decision Models for Business and Economics	MoTuWeThFr 9:45AM - 11:15AM	Peter Lin	Hanes Hall - Rm 0107	11/30 (30 total)	Seats filled
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.
1734	STOR 113 - 002 Decision Models for Business and Economics	MoTuWeThFr 11:30AM - 1:00PM	Andrew Ackerman	Hanes Hall - Rm 0107	Seats filled (15 total)	Seats filled
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.
1735	STOR 120 - 001 Foundations of Statistics and Data Science	MoTuTh 9:45AM - 11:45AM	Jeff McLean	Hanes Hall - Rm 0130	14/30 (30 total)	Seats filled
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.
1736	STOR 120 - 002 Foundations of Statistics and Data Science	MoTuTh 1:15PM - 3:15PM	Jeff McLean	Hanes Hall - Rm 0130	22/30 (30 total)	Seats filled
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.
1746	STOR 120 - 400 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Daniel Meskill	Hanes Hall - Rm 0112	Seats filled (7 total)	Seats filled
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.
1745	STOR 120 - 401 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Hui Shen	Gardner - Rm 0001	Seats filled (7 total)	Seats filled
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.
1744	STOR 120 - 402 Foundations of Statistics and Data Science	WeFr 1:15PM - 2:10PM	Daniel Meskill	Hanes Hall - Rm 0107	11/13 (13 total)	Seats filled
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.
1743	STOR 120 - 403 Foundations of Statistics and Data Science	WeFr 1:15PM - 2:10PM	Hui Shen	Dey Hall - Rm 0307	11/13 (13 total)	Seats filled
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.
1737	STOR 155 - 001 Introduction to Data Models and Inference	MoTuWeThFr 9:45AM - 11:15AM	Oluremi Abayomi	Hanes Hall - Rm 0125	15/18 (18 total)	Seats filled
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.
1738	STOR 155 - 002 Introduction to Data Models and Inference	MoTuWeThFr 9:45AM - 11:15AM	WILLIAM LASSITER	Hanes Hall - Rm 0120	9/20 (20 total)	Seats filled
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.
1739	STOR 155 - 003 Introduction to Data Models and Inference	MoTuWeThFr 11:30AM - 1:00PM	Oluremi Abayomi	Hanes Hall - Rm 0125	19/20 (20 total)	Seats filled
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.
1740	STOR 155 - 004 Introduction to Data Models and Inference	MoTuWeThFr 1:15PM - 2:45PM	WILLIAM LASSITER	Hanes Hall - Rm 0125	17/20 (20 total)	Seats filled
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.
1741	STOR 435 - 001 Introduction to Probability	MoTuWeThFr 9:45AM - 11:15AM	CHUANSHU JI	Gardner - Rm 0105	14/50 (50 total)	Seats filled
Description: Prerequisite, MATH 233. 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.
1742	STOR 435 - 002 Introduction to Probability	MoTuWeThFr 11:30AM - 1:00PM	CHUANSHU JI	Gardner - Rm 0105	9/50 (50 total)	Seats filled
Description: Prerequisite, MATH 233. 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.