FAQs

If you are applying at the end of year 1 and hope to be a Statistics major with year 2 standing, please follow the procedure at http://www.science.ubc.ca/students/degree/apply.
You should list Statistics among your top 3 choices. If you ask for Statistics as a top choice and didn't get this choice, please go to the next item.

If you are in year 2, follow the recommended courses listed in the academic calendar for the Statistics specialisation that you are interested in: for example, Major in Statistics, Combined Major CPSC/Statistics, Combined Major Statistics/Economics.
Take Math 200 (multivariable calculus), Math 221 (linear or matrix algebra) and Math/Stat 302 (introductory probability) as soon as possible. Then read the next item.

We assume that you are in year 2 or later. You can apply via the online form at: https://ubc.ca1.qualtrics.com/jfe/form/SV_0MQQzD5Bq1wqtyl after you have completed Stat 200 (introductory statistics), Math 200(multivariable calculus), Math 221 (linear algebra) and Math/Stat 302 (introductory probability) with decent grades.

Please read the instructions carefully before submitting your application. Applications will be considered in January and in May each year by the reviewing of overall profiles and grades in relevant Computer Science, Mathematics, and Statistics courses.
The application deadlines are mid-January and mid-May. Entry to the Statistics major is competitive. For any further inquiries such as Major in Mathematical Sciences, please contact an advisor at latemajorentrants at stat dot ubc dot ca.

If you have continued to take Stat / Math courses at the 300 level and above, and your grades have improved, then you can apply again at:
https://ubc.ca1.qualtrics.com/jfe/form/SV_0MQQzD5Bq1wqtyl

Please see the Department of Economics find web link for more information. The deadline to apply is around May 20th.
https://economics.ubc.ca/undergraduate/programs/majorscombined-majors-pr...

You would have to apply to the CPSC Department. For the form, please see https://www.cs.ubc.ca/students/undergrad/prospective/switching/computer-.... It opens in April, and is closed for parts of the year.

If you are in year 3, there is a deadline in early October. If you are in year 2, there is a deadline in early March.
Please see web site https://sciencecoop.ubc.ca/prospective/apply/statistics for instructions, qualifications and possible schedules for co-op terms.

For Major in Statistics and Combined Major with Statistics: an average of at least 60% on their first attempts in their best 3 of the 5 "named" courses in Year 2. These five "named" courses in Year 2 are: MATH 200, MATH 220, MATH 221, STAT 200, and STAT/MATH 302. STAT 200 (or equivalent) must be completed for promotion to year 3.

STAT 305 and STAT 306 (or ECON 326 for the BA Combined Major in Econ/Stat) must be completed for promotion to year 4. Please also see the Faculty of Science general requirements for promotion. For example:
http://www.calendar.ubc.ca/vancouver/index.cfm?tree=12,215,410,1467#18475

Take them as soon as possible but not necessarily by the end of year 2 if there are registration issues.
Credit for CPSC 110 and one of CPSC 210 or Math 210 is required for promotion to year 4.

Yes, if you have credit for Math 200 and Math 221 (or their equivalents), and can fit in the Science breadth requirements and the thematic concentation requirements.
For example, take STAT/MATH 302, Stat 300, Stat 344 in term 1 of year 3; STAT 305, Stat 306 in term 2 of year 3. Then you have the prerequisites for Stat 400 level courses.

The requirement for a minor in statistics is 18 upper-level STAT credits, which may include MATH 302 in place of STAT 302.

If you are in a BSc program, please see the form at https://science.ubc.ca/students/forms
If you are in a BA program, consult https://students.arts.ubc.ca/specializations/adding-a-minor/
If you are a Commerce major, consult an advisor in the Undergraduate Office in the Sauder School of Business to get a form. https://www.sauder.ubc.ca/programs/bachelors-degrees/home/contact-us

For 2019-2020 (and likely for near future):
- Stat 344, 404, 406: offered only in term 1.
- Stat 443, 450: offered only in term 2.
- Stat 300, 305 and 306 offered in terms 1 and 2.
- Stat/Elec 321 offered in terms 1 and 2.
- Stat 302 in terms 1 and 2, and the summer term.

Stat 200, Stat 251 and Stat 302 are offered in terms 1 and 2 and the summer term. Stat 203 (for non-science students) is offered in term 1 only.

Introductory probability requires multivariable calculus (e.g. Math 200) as a prerequisite and is much more mathematical than an introductory statistics course. Introductory Statistics courses involve data analysis and statistical software, whereas Introductory probability courses do not.

Example of an exam question in introduction probability:
An insurance policy pays a total medical benefit consisting of two parts for each claim. Let X represent the part of the benefit that is paid to the surgeon, and let Y represent the part that is paid to the hospital. The variance of X is 4000, the variance of Y is 8000, and the variance of the total benefit, X+Y, is 14000.
(a) What is the covariance of X and Y?
(b) Due to increasing medical costs, the insurance company decides to increase X by a flat amount of 100 per claim and to increase Y by 10% per claim. Calculate the variance of the total benefit after these revisions have been made.

Example of an exam question in introductory statistics. Physical fitness testing is an important aspect of athletic training. A common measure of the magnitude of cardiovascular fitness is the maximum volume of oxygen uptake during a strenuous exercise. A study was conducted on 24 middle-aged men to study the influence of the time that it takes to complete a 3 km run on the oxygen uptake. The scatter diagram of oxygen uptake against time is roughly oval-shaped. The regression analysis for the data is summarized as [... not repeated here].
(a) Predict the maximum volume of oxygen intake, when the time takes to complete 3 km run is (i) 700 seconds and (ii) 1120 seconds.
(b) Does the time it takes to run a distance of three km's have a significant influence on maximum oxygen intakes (answer with yes or no and explain in no more than 20 words)?

Stat 200 (or any introductory statistics course) and Stat/Math 302 (introductory probability).
Math 200 (multivariate calculus) is a prerequisite for Stat 302.
Math 221 or Math 223 (linear algebra) is a prerequisite for Stat 306.
Note that Stat 251 is an introductory course on probability and statistics (so less Statistics than Stat 200 and less probability than Stat/Math 302).
Stat 251 is NOT acceptable as a prerequisite (in place of Stat 302) for any Stat course numbered 305 and above, other than ELEC/Stat 321 (Stochastic Signals and Systems).

The field of Statistics is quite interdisciplinary because statistical methodology is used in all areas where research studies are carried out, data are collected, and statistical analyses are done to make comparisons, predictions and forecasts.

The study of statistics can be combined with business, data science, economics, finance, genomics, health studies, insurance, pharmaceutical science, etc.

The Statistician's work can vary from a focus on application areas (requires knowledge of subject areas), to theoretical development of methodology (requires advanced mathematics) and the development of statistical software (requires skills in scientific programming).

Data science focuses on data visualization, data management, data analytics and large databases; data scientists should understand variation and uncertainty, representativeness, efficient data collection, meaningful data reduction and summarization, and analytic tools from different sciences. Good reference: http://www.ThisisStatistics.org

Here are some possible careers (job titles) with their qualifications.
1. Career with quantitative analysis, such as actuary, benefits analyst, insurance underwriter, market research analyst, data scientist, survey analyst. Qualifications: BSc in Statistics (A/B average) with communications skills, computing/coding skills.
2. A.Stat designation from Statistical Society of Canada, https://ssc.ca/en/accreditation. This could be useful for statistical project work as a consultant. Qualifications: courses in Statistics major with grades exceeding B-.
3. Job title of statistician. Qualifications: MSc in Statistics, which requires BSc with A average (maybe B+ minimum) with harder courses in Statistics/Mathematics.
4. Job title of biostatistician (health-related), Qualifications: MSc in Statistics/Biostatistics.

Input something like "top careers 2019" into a search engine. Here are some results. https://money.usnews.com/careers/best-jobs/rankings/the-100-best-jobs
#1 Software developer (Education Bachelor's)
#2 Statistician. (Education Master's)
#17 Mathematician. (Education Master's)
#24 Accountant. (Education Bachelor's)
#25 Financial Manager. (Education Bachelor's)
#27 Computer Systems Analyst. (Education Bachelor's)
#33 Actuary (Education Bachelor's)
#34 Operations Research Analyst (Education Bachelor's)
#60 Market Research Analyst (Education Bachelor's)

Please see the next few items for quotes from various sources.

Confucius saying: I hear and I forget; I see and I remember; I do and I understand. That is, there is a big difference between memorization and understanding. To achieve understanding, you have to DO enough textbook examples/exercises and homework problems to grasp the steps of logical reasoning.

Advice from AmStat News, in an interview with Greg Campbell, biostatistician in the US Federal Government.
Most biostatistical jobs require at least a Master's degree on statistics or biostatistics, so one is well-advised to take lots of courses. I personally adhere to the philosophy that good applied statisticians need a solid mathematical underpinning. This will enable one to be undaunted in picking up a journal article with formulas in it or to innovate if the problem does not quite fit the textbook example. So, my other advice is to take a variety of coursework in order to expand your toolbox. And, of course, education need not end at the university; it can be a lifelong passion.

Advice From a document at the Department of Mathematics and Statistics, University of Victoria. Compiled by Gary MacGillivray

(a) Be responsible for your own learning. Know your own learning style and use it in studying. Don't give up on concepts you don't understand. It is never too late. Mathematics is logical and cumulative. The more material from previous courses and from earlier in current courses that you understand, the better equipped you are to understand what comes next, connect it to other material, and apply it in different contexts.

(b) Get out a pencil and paper, and try to work through every step of each example or proof rather than trying to read your text or notes like a novel. If you get stuck, don't give up.

(c) Understanding beats memorizing. If you understand, then you'll remember. Unfortunately, it doesn't work the other way around. The first step in grasping a definition or theorem is being able to write it down, precisely, without any help. Trying to apply concepts when you're struggling to remember what the words mean is a tough battle. Be kind to yourself. Learn the vocabulary and the methods.

(d) Learn from your mistakes. If you make a mistake, try to understand what went sideways, and then take steps to improve your understanding of that. Keep going until you're atisfied that you really understand. Go over returned class work and try to take advantage of the feedback you've been given. It will help you identify concepts or techniques that need more attention. Do the same with practice questions.

(e) Get help right away. When you're having trouble with something, go for help on the same day if possible, and don't wait longer than the next day that help is available.

(a) Achieve in practice. Remember that, in the end, it is necessary to answer questions by yourself without any help. Prepare for that by learning the material and developing your skills. Keep trying. If you're working through practice questions and get one wrong, keep coming back to it and similar questions until you can do them yourself. Reading someone else's solution, or getting help from another person, can give insights and helpful pointers to things that need work, but that's only part of what's needed. Like swimming or cycling, mathematics is something that you do. It is tough to learn how by reading about it or watching someone else. When you have learned the concepts, and accumulated a lot of experience using them through regular practice, you'll have confidence in your abilities. Keep your goals in focus.

(b) Start early. Begin thinking about assignments the day you get them. It takes time to think about the questions and how the different methods you know might apply. Start studying for tests at least four or five days beforehand. This will give you lots of time to fill in any blanks in your understanding.

(c) Always start with things you can do. Look over all of the questions on every assignment or test and pick the low-hanging fruit first. Build on success.

(a) Pre-reading: I try to go through the pre-readings for the next class a day in advance. I don’t necessarily aim to understand everything, but rather get familiar with the material. I find the lectures to be much easier to follow this way.
(b) Formulas: I always derive the formulas and equations introduced in the class at least once, in a way that I am most comfortable with, which might take a different form than the ones introduced in class. This for the most part saves me from memorizing them and ensures understanding of the material.
(c) Note taking in class: I don’t think it’s enough to just listen in a lecture, no matter how focused I am. A lot of the times, it is not the things on the slides, but rather the professor’s explanations to what’s on the slides that help me understand the material. I write these things down in class, as quite often, these things are not documented in any of the materials provided for the class.

(d) Review notes: before each midterm and final exam, I always read the slides and textbook, and make a set of review notes. This includes key concepts, important derivations, and simple examples. I find myself understanding the material much better after writing the important things down neatly. I put more emphasis on things that I am confused about and refer to this set of notes through my exam prep period.
(e) Questions: while I make my review notes, I write down any questions that I come up with beside the corresponding section of the notes. After the notes are completed, I come back to these questions and see if I can answer them having gone through all of the materials covered.
(f) Exam and homework problems: I always keep all of my returned midterms and homework sets. I think it’s important to look back at the problems I have done after a while. For the questions I got wrong, I analyze what caused the mistakes and make sure I understand the concept so that I can avoid making the same mistakes again. For the questions I got right, they can serve as a good refresher to the concepts that might not have been touched on for a while.

(g) Material from prerequisite courses. With regard to material from previous courses, I don't really take any time before the start of a course to review the prerequisite material, but do actively refer to notes/textbooks on those topics throughout the term, especially in the beginning, to help with the current course. Based on my experience there are usually only a few things from a previous course that are heavily used, and by going back to the notes on those topics in the beginning of the term, I usually find it to be quite manageable. Sometimes the same concepts are taught in a different perspective, and I think it's important to build that connection between the different interpretations.

Likely yes. Try to find the closest UBC-V course based on course descriptions given below.

Likely Stat 200, assuming a statistical software was used and some topics/vocabulary included: histogram, boxplot, mean, standard deviation, median, scatterplot, correlation, confidence interval, hypothesis testing, P-value, regression.

Likely Stat 203, assuming some topics/vocabulary included: histogram, boxplot, mean, standard deviation, median, scatterplot, correlation, confidence interval, hypothesis testing, P-value, regression.

Likely Stat/Math 302, assuming some topics/vocabulary included: discrete and continuous probability distributions, conditional probability, binomial coefficient, hypergeometric distribution, negative binomial distribution, gamma function, gamma distribution; expected value, variance and covariance of linear combinations of random variables; probability calculations via double integrals. Also a course objective is that you can solve probability problems such as the probability of different patterns in 5-card poker.

Likely Stat 251 (also the previous equivalent Stat 241): this course cover less topics of statistical methods compared with Stat 200 and less on probability theory compared with Stat 302. Some topics/vocabulary in this course are: discrete and continuous probability distributions, conditional probability, expectation, sampling distributions, estimation and testing.

We assume multivariable calculus was a prerequisite. Courses in China typically have between 48 and 54 contact hours in a term, so your course covers more than Stat 302, and includes part of Stat 305 at UBC-V. You can ask for transfer credit for Stat/Math 302.

In China, the second course in theoretical statistics typically contains the material in Stat 305 at UBC-V. However the practice of applied statistics and the use of statistical software may have been omitted; in this case, consider taking Stat 200 at UBC-V, but ask for Stat 305 credit.

We are hoping that instructions for appeal will be provided at https://students.ubc.ca/enrolment/registration/transfer-credits/post-sec... Please check this item later for an update.