- International Fees
International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.
Course details
This hands-on course follows on from MATH 1060 - Statistics for Data Analysis and introduces the students to many of the techniques used in the field of data analytics. This introduction will enable students to use general classification and predictive analysis methods. Methods appropriate for scientific data are also discussed. Labs and projects using the open source statistical analysis tool, R, build on the skills learned in Math 1060 to apply these advanced techniques. Upon successful completion, students will be able to effectively analyze large and small data sets while adhering to sound statistical principles. This course is required for COMP 4254 in the Applied Data Analytics Certificate offered by BCIT Computing.
Prerequisite(s)
- 60% in MATH 1060
Credits
4.0
Domestic fees
$775.69
Course offerings
Spring/Summer 2024
Below is one offering of MATH 3060 for the Spring/Summer 2024 term.
CRN 65337
Duration
Sat Apr 06 - Sat Jun 22 (12 weeks)
- 12 weeks
- CRN 65337
- Domestic fees $775.69International fees are typically three times the amount of domestic fees.
Class meeting times
| Dates | Days | Times | Locations |
|---|---|---|---|
| Apr 06 - May 04 | Sat | 09:30 - 12:30 | Online |
| May 11 | Sat | 09:30 - 12:30 | Burnaby SW03 Rm. 3655 |
| May 18 - Jun 15 | Sat | 09:30 - 12:30 | Online |
| Jun 22 | Sat | 09:30 - 12:30 | Burnaby SW03 Rm. 3655 |
Instructor
Takashi Nakamura
Course outline
Domestic fees
$775.69
Important information
- International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.
-
**IMPORTANT: Prerequisite is MANDATORY and will be verified - NO EXCEPTIONS. Course information will be sent to you prior to your course start date. Check your myBCIT email account access this information. If you have any questions about your pre-requisite, please email mathpts@bcit.ca. THIS COURSE WILL BE DELIVERED WITH ONLINE LECTURES AND IN-PERSON TEST. On the start date of your class (not before), log into learn.bcit.ca to access your course link. This class meets once per week for 3 hours in a virtual classroom AND requires an additional 1 hour per week as an online component. Course is 48 hours – 36 in class and 12 online. Midterm: May 11th
Status
In Progress
This course offering is in progress. Please check back next term, subscribe to receive email updates or contact us with your comments or questions.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Compute confidence regions and perform basic hypothesis testing with multivariate normal distributions.
- Perform dimensionality reduction of high-dimensional data sets using principal component analysis.
- Describe principles of various regression and classification/clustering algorithms.
- Apply appropriate classification algorithms for problems at hand.
- Describe principles of various time series analysis methods.
- Apply appropriate time series analysis for problems at hand.
- Apply basic Bayesian statistics in decision making and risk assessment.
- Describe principles of neural network algorithms.
- Adopt constantly-evolving new tools (algorithms).
Effective as of Fall 2016
Related Programs
Advanced Statistical Techniques for Data Analytics (MATH 3060) is offered as a part of the following programs:
- Indicates programs accepting international students.
- Indicates programs with a co-op option.
School of Computing and Academic Studies
- Applied Data Analytics
Certificate Part-time
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