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DANA 4810: Predictive Analytics - Quantitative Data

Course FormatLecture 3.0 h + Seminar 0.0 h + Lab 1.0 h
Credits3.0

Predictive analytics is a process of using and applying statistical analysis techniques for estimation and forecasting. Students learn standard methodology for analyzing quantitative data, including analysis of variance, design of experiments, simple regression, multiple regression, data transformation, and generalized linear models.

Registration in this course is restricted to students admitted to the Post-Degree Diploma in Data Analytics and Post-Degree Certificate in Data Analytics.

Prerequisite(s): A passing mark from Data Analytics Math Assessment Test or an "S" grade in MATH 4801; and a minimum "C" grade in DANA 4800.


Course Attributes:
2nd Year Arts
2nd Year Science
Humanities
Lab Science
Science
Social Science
University
Transferable
Other Attributes:
Offered online:No
Preparatory course:No
Repeat limit2
Additional fees:$34.3
First offered:Summer 2019
Last offered:Fall 2025
Registration
restrictions:		RP
Outline(s):

DANA 4810 - Summer 2019 (v. 2)

Transfer Agreements
CourseDestinationCreditStart to End
No active transfer agreements.
Inactive Transfer Agreements (click to open)
CourseDestinationCreditStart to End
No inactive transfer agreements.

Offerings of this course:

SemesterCRNSectionSeatsWaitlistDaysTimeRoomTypeInstructor
Fall 20253080500131N/A-T-R---1430-1620 Lecture. TBA
Summer 20252028800115 -T-R---1430-1620B155LectureNooshin Lary
Spring 20251012900112 -T-R---1430-1620A322LectureAzadeh Alimadad
-----S-0900-1155B030ExamAzadeh Alimadad
Fall 2024304660019 -T-R---1430-1620B152LectureAzadeh Alimadad
--W----1830-2125B152ExamAzadeh Alimadad
Summer 2024207060014 ---R---1230-1420B010LectureNooshin Lary
--W----1630-1820B022LectureNooshin Lary
--W----1830-2125B010ExamNooshin Lary
Spring 2024109930015 M-W----1030-1220B153LectureAzadeh Alimadad
M------1830-2125B030ExamAzadeh Alimadad
Fall 2023303560015 M-W----1430-1620A374LectureAzadeh Alimadad
-T-----1830-2125A374ExamAzadeh Alimadad
Summer 20232057800110 M-W----1430-1620B153LectureNooshin Lary
-T-----1830-2125B153ExamNooshin Lary
Spring 20231084400114 -T-R---1430-1620B023LectureQuynh Nguyen
-T-----1830-2125B023ExamQuynh Nguyen
Fall 2022306680019 -T-R---1430-1620A215LectureNooshin Lary
--W----1830-2125A215ExamNooshin Lary
Summer 2022204660017 -T-R---1430-1620B029LectureQuynh Nguyen
-T-----1830-2125B029ExamQuynh Nguyen
Spring 2022110580017 -T-R---1630-1820B031LectureQuynh Nguyen
--W----1830-2125B031ExamQuynh Nguyen
Fall 202130168W0110 -T-R---1630-1820WWWWWWQuynh Nguyen
----F--1830-2125WWWExamQuynh Nguyen
Summer 202120570W014 M-W----1630-1820WWWWWWQuynh Nguyen
M------1830-2125WWWExamQuynh Nguyen
Spring 202110942W0116 M-W----1830-2020WWWWWWQuynh Nguyen
--W----1830-2125WWWExamQuynh Nguyen
Summer 202021156W011 M-W----1830-2020WWWWWWQi Wen
--W----1830-2125WWWExamQi Wen
Spring 2020114950013 M-W----1830-2020B023LectureQi Wen
M------1830-2125B031ExamQi Wen
Summer 2019206870011 M-W----1830-2020B155LectureNathaniel Payne
---R---1830-2125B247ExamNathaniel Payne