STOR Courses

Here is information about STOR class enrollment for summer II 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 15:58:54.004348

Class Number	Class	Meeting Time	Instructor	Room	Unreserved Enrollment	Reserved Enrollment	Total Enrollment	Wait List
2099	STOR 113 - 001 Decision Models for Business and Economics	MoTuWeThFr 11:30AM - 1:00PM	Panagiotis Andreou	Hanes Hall-Rm 0130	13/30	Seats filled	13/30	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.
2102	STOR 115 - 001 Reasoning with Data: Navigating a Quantitative World	MoTuWeThFr 9:45AM - 11:15AM	Hank Flury	Davie Hall-Rm 0301	2/10	Seats filled	2/10	0/999
Description: Students will use mathematical and statistical methods to address societal problems, make personal decisions, and reason critically about the world. Authentic contexts may include voting, health and risk, digital humanities, finance, and human behavior. This course does not count as credit towards the psychology or neuroscience majors. 3 units.
2103	STOR 120 - 001 Foundations of Statistics and Data Science	MoTuTh 9:45AM - 11:45AM	Andrew Ackerman	Hanes Hall-Rm 0107	17/34	Seats filled	17/34	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.
2104	STOR 120 - 400 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Akshay Sakanaveeti	Hanes Hall-Rm 0107	10/20	Seats filled	10/20	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.
2105	STOR 120 - 401 Foundations of Statistics and Data Science	WeFr 9:45AM - 10:40AM	Kyung Rok Kim	Dey Hall-Rm 0203	7/20	Seats filled	7/20	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.
1288	STOR 155 - 001 Introduction to Data Models and Inference	MoTuWeThFr 9:45AM - 11:15AM	Trung Nghia Nguyen	Hanes Hall-Rm 0120	16/30	Seats filled	16/30	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.
1289	STOR 155 - 002 Introduction to Data Models and Inference	MoTuWeThFr 11:30AM - 1:00PM	Tianzhu Liu	Hanes Hall-Rm 0125	7/30	Seats filled	7/30	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.
1290	STOR 155 - 003 Introduction to Data Models and Inference	MoTuWeThFr 1:15PM - 2:45PM	Sumit Kumar Kar	Hanes Hall-Rm 0125	20/30	Seats filled	20/30	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.
1291	STOR 320 - 001 Introduction to Data Science	MoTuWeTh 12:45PM - 2:45PM	Kendall Thomas	Hanes Hall-Rm 0120	26/30	Seats filled	26/30	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.
1293	STOR 320 - 400 Introduction to Data Science	Fr 12:45PM - 2:45PM	Dilshad Imon	Hanes Hall-Rm 0107	14/15	Seats filled	14/15	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.
1294	STOR 320 - 401 Introduction to Data Science	Fr 12:45PM - 2:45PM	Coleman Ferrell	Dey Hall-Rm 0405	12/15	Seats filled	12/15	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.
1297	STOR 455 - 001 Methods of Data Analysis	MoTuWeThFr 1:15PM - 2:45PM	Andrew Ackerman	Hanes Hall-Rm 0130	25/30	Seats filled	25/30	0/999
Description: Prerequisite, STOR 120, or 155. Review of basic inference; two-sample comparisons; correlation; introduction to matrices; simple and multiple regression (including significance tests, diagnostics, variable selection); analysis of variance; use of statistical software. 3 units.