Maryam Hasanzadeh Mofrad
Fall Term 2024 (1890)
MGTSC 212 - Probability and Statistics for Business
3 units (fi 6)(EITHER, 3-0-1)
This course deals with model building, multiple regression analysis, and related methods useful in a business environment. Microcomputer software will be utilized throughout the course, with necessary computing skills being taught as the course proceeds. However, students are expected to already possess some basic familiarity with microcomputer applications. Prerequisite: STAT 161 or equivalent. Credit will be granted for only one of MGTSC 212 (formerly MGTSC 312) and STAT 252. Students may not receive credit for both MGTSC 212 and MGTSC 312.
LAB D07 (46219)
2024-09-03 - 2024-12-09
T 15:00 - 15:50
2024-09-03 - 2024-12-09
T 15:00 - 15:50
LAB D01 (46221)
2024-09-03 - 2024-12-09
R 14:00 - 14:50
2024-09-03 - 2024-12-09
R 14:00 - 14:50
LAB D06 (46224)
2024-09-03 - 2024-12-09
R 15:00 - 15:50
2024-09-03 - 2024-12-09
R 15:00 - 15:50
LAB D08 (50593)
2024-09-03 - 2024-12-09
R 12:00 - 12:50
2024-09-03 - 2024-12-09
R 12:00 - 12:50
LAB D09 (51556)
2024-09-03 - 2024-12-09
T 13:00 - 13:50
2024-09-03 - 2024-12-09
T 13:00 - 13:50
LAB D10 (52350)
2024-09-03 - 2024-12-09
T 10:00 - 10:50
2024-09-03 - 2024-12-09
T 10:00 - 10:50
LAB D11 (52351)
2024-09-03 - 2024-12-09
R 13:00 - 13:50
2024-09-03 - 2024-12-09
R 13:00 - 13:50
LAB D13 (53871)
2024-09-03 - 2024-12-09
R 10:00 - 10:50
2024-09-03 - 2024-12-09
R 10:00 - 10:50
LAB D14 (53872)
2024-09-03 - 2024-12-09
T 14:00 - 14:50
2024-09-03 - 2024-12-09
T 14:00 - 14:50
OM 420 - Predictive Business Analytics
3 units (fi 6)(EITHER, 3-0-0)
Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 352 or OM 352.
LECTURE A01 (49387)
2024-09-03 - 2024-12-09
MW 11:00 - 12:20
LECTURE A02 (49388)
2024-09-03 - 2024-12-09
MW 14:00 - 15:20
OM 620 - Predictive Business Analytics
3 units (fi 6)(EITHER, 3-0-0)
Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 501.
LECTURE A01 (49389)
2024-09-03 - 2024-12-09
MW 11:00 - 12:20
Winter Term 2025 (1900)
MGTSC 212 - Probability and Statistics for Business
3 units (fi 6)(EITHER, 3-0-1)
This course deals with model building, multiple regression analysis, and related methods useful in a business environment. Microcomputer software will be utilized throughout the course, with necessary computing skills being taught as the course proceeds. However, students are expected to already possess some basic familiarity with microcomputer applications. Prerequisite: STAT 161 or equivalent. Credit will be granted for only one of MGTSC 212 (formerly MGTSC 312) and STAT 252. Students may not receive credit for both MGTSC 212 and MGTSC 312.
LECTURE B02 (77430)
2025-01-06 - 2025-04-09
TR 14:00 - 15:20
LAB H02 (77431)
2025-01-06 - 2025-04-09
R 11:00 - 11:50
2025-01-06 - 2025-04-09
R 11:00 - 11:50
OM 420 - Predictive Business Analytics
3 units (fi 6)(EITHER, 3-0-0)
Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 352 or OM 352.
LECTURE B01 (71699)
2025-01-06 - 2025-04-09
MW 11:00 - 12:20
LECTURE B02 (77905)
2025-01-06 - 2025-04-09
TR 12:30 - 13:50
OM 620 - Predictive Business Analytics
3 units (fi 6)(EITHER, 3-0-0)
Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 501.
LECTURE B01 (71694)
2025-01-06 - 2025-04-09
MW 11:00 - 12:20