Mathematics and Statistics

Data Analysis Post-baccalaureate certificate

Data analysis is the science of correctly collecting data, assessing it for trustworthiness, extracting information from it, and presenting it in a comprehensible informative way. These skills are vital to institutions such as government, business, or health care where sound decisions must be made based on data and the way it is interpreted.

Students will acquire the skills needed to extract reliable information from large data sets. With carefully designed courses taken in both computing and statistics, students will gain the data-base skills needed to house, extract, manipulate, and maintain data, and will learn the statistical techniques needed to collect data correctly, assess its quality, analyze it, and present the information effectively to decision makers. The industry standard statistical software environments SAS and R will be used throughout.

Entrance requirements

1. A Bachelor's degree from a recognized institution.

Note: Students currently earning a university degree may enrol in the courses of the Data Analysis Post-baccalaureate certificate, provided they meet the course-prerequisites. They will be granted credit for having completed the certificate when they have met its requirements, and have fulfilled the requirements of their degree.

2. One of the following programming courses:

• COMP 150, Introduction to Programming
• COMP 152, Introduction to Structured Programming
• COMP 155, Object Oriented Programming (recommended)

3. Applicants must meet the Degree/diploma level English language proficiency requirement. For details on how this requirement may be met, see the English language proficiency requirement section of the calendar.

When to apply

Applications are accepted for entrance to the late Summer (July/August) semester. For application deadlines, see Specific intake application process.

How to apply

Apply online at ufv.ca/admissions/admissions/apply.

Additional documents required for a complete application:
• Official transcripts (or interim transcripts) of all post-secondary institutions attended showing grade/course achievement as per program entrance requirements. To be considered official, transcripts must be sent directly to UFV from the originating institution; see the Transfer Credit section for details.

Fees and additional costs

See the Fees and Other Costs section.

Program requirements

Students must complete ten courses, for a total of 31 credits. The certificate can be earned in about one year, beginning in July and ending in June. Those students who have credit for STAT 106 (with a B or better) or MATH 270/STAT 270 can earn the certificate in about ten months, beginning in
September and ending in June.

Required courses:

Three courses chosen from the following:

Course repetition

A maximum of three repeated courses are permitted without dean’s approval.

Residency

At least 21 credits toward the certificate must be taken at UFV.

Undergraduate continuance

Students enrolled in undergraduate courses (courses numbered 100 or above) must maintain an undergraduate Cumulative Grade Point Average (CGPA) of at least 2.00 to remain enrolled in Good Academic Standing at UFV. Students in Good Academic Standing will have no registration limits placed on them. Failure to meet the minimum CGPA requirement will result in restrictions on registration and may eventually lead to academic suspension from undergraduate studies at UFV. Students on Academic Warning or Academic Probation are limited to registering in 10 credits. For further details, see the Academic standing and undergraduate continuance section of the academic calendar. Academic standing is governed by UFV’s Undergraduate Continuance policy (92).

Graduation requirements

Students must have a minimum GPA of 2.0 on all ten courses (31 credits) required to complete the program.

To graduate from the data analysis certificate, students must have completed the requirements of a university degree.

Course listings

For complete details on courses see the course descriptions section.