Figure 1 Public Sector Universe

Figure 1 Public Sector Universe
Description for Figure 1

The hierarchy of the public sector along with its subcomponents.

Public sector:

  • General governments
    • Federal general government
      • Government
        • Ministries and departments, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • Federal non-autonomous pension plans
    • Social Security FundsFootnote 1
      • Canada Pension Plan
      • Quebec Pension Plan
    • Provincial and territorial general government
      • Government
        • Ministries and departments, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • Provincial non-autonomous pension plans
      • Universities and colleges
      • Health and social service institutions
    • Local general government
      • Government
        • Municipalities and quasi-municipalities, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • School boardsFootnote 2,Footnote 3
    • Aboriginal general government
      • Government
        • Aboriginal governments
  • Government business enterprises
    • Federal government business enterprises
    • Provincial and territorial government business enterprises
    • Local government business enterprises

Footnotes

How to Make an Access to Information Request or a Personal Information Request

You can submit your Access to Information or Privacy request online or by mail.

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Using the ATIP online Request service, is a faster, easier and more convenient way to submit access to information or privacy requests. Apply online today to save time and postage.

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Before you make a Request

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Access to Information Request Form

Personal Information Request Form

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Office of Privacy Management and Information Coordination
Statistics Canada
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North American Product Classification System (NAPCS) Canada 2012 Version 1.1

Introduction

NAPCS Canada 2012 Version 1.1 updates NAPCS Canada 2012 Version 1.0. In total, there are 271 changes between the two versions. Some categories were split, and others were merged. New categories were incorporated, and some were deleted, for a net addition of 65 product categories at different levels, providing better alignment with survey data collection and publication. In some instances, these modifications created the need to renumber codes. These changes account for about half of the update. The remaining changes relate to editing of class titles adding precision to their formulations. The detailed list of changes can be obtained from Standards Division at standards-normes@statcan.gc.ca.

Standard classification structure

The standard classification structure of NAPCS Canada 2012 comprises four levels: group, class, subclass, and detail. The table below outlines the nomenclature and provides the number of categories within each level of NAPCS Canada 2012 versions 1.1 and 1.0.

Standard classification structure of NAPCS Canada 2012
Level Coding Number of categories NAPCS 2012 Version 1.1 Number of categories NAPCS 2012 Version 1.0
Group 3-digit codes 158 158
Class 5-digit codes 511 510
Subclass 6-digit codes 1,402 1,398
Detail 7-digit codes 2,694 2,648
Table source: Statistics Canada, NAPCS.

Classification variants

Along with NAPCS Canada 2012 Version 1.1, two new regrouping variants are made available: one for the Industrial Product Price Index (IPPI) and one for the Raw Materials Price Index (RMPI). These variants add one level (section) above the standard classification structure; this new level is defined in terms of standard groups (three-digit). The tables below illustrate the nomenclature of the IPPI and RMPI variants and provide the number of categories within each level.

Levels for IPPI variant
Levels for IPPI variant Coding Number of categories
Section 3-character alphanumeric codes 21
Group 3-digit standard codes, and 4-character alphanumeric codes 79
Class 5-digit standard codes, and 6-character alphanumeric codes 241
Subclass 6-digit standard codes 665
Detail 7-digit standard codes 1,190
Table source: Statistics Canada, NAPCS.
Levels for RMPI variant
Levels for RMPI variant Coding Number of categories
Section 3-character alphanumeric codes 6
Group 3-digit standard codes, and 4-character alphanumeric codes 21
Class 5-digit standard codes, and 6-character alphanumeric codes 44
Subclass 6-digit standard codes 90
Detail 7-digit standard codes 197
Table source: Statistics Canada, NAPCS.

At the time of publishing this note, the plan is to create two regrouping variants for capital expenditures and one extension variant for agricultural products.

Status

This standard was approved as a departmental standard on January 16, 2007.

2006 version of the SGC

The Standard Geographical Classification (SGC) is Statistics Canada's official classification of geographic areas in Canada. The SGC provides unique numeric codes for three types of geographic areas: provinces and territories, census divisions (counties, regional municipalities), and census subdivisions (municipalities). The three geographic areas are hierarchically related; a seven-digit code is used to show this relationship. In addition to the SGC units, metropolitan areas with their component census subdivisions and economic regions with their component census divisions are included.

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Concordances and documentation on changes

Other geographical entities

Changes to SGC 2006

Reference Maps

The Standard Geographical Classification (SGC) is Statistics Canada's official classification of geographic areas in Canada. The SGC provides unique numeric codes for three types of geographic areas: provinces and territories, census divisions (counties, regional municipalities), and census subdivisions (municipalities). The three geographic areas are hierarchically related; a seven-digit code is used to show this relationship. In addition to the SGC units, metropolitan areas with their component census subdivisions are included.

More information

Five-Year Survival Estimates for Cancer using the Cohort Approach – Key Methodological Points

Survival after a diagnosis of cancer is affected by a variety of individual, tumour and healthcare system factors. Individual factors include sex, age at diagnosis, comorbidity, socioeconomic status and lifestyle; tumour-related factors include histological subtype, aggressiveness of the tumour, and spread of disease at diagnosis; and, healthcare system factors include the availability and quality of early detection, diagnostic and treatment services. Examined across cancer types and regions, survival estimates can be used to establish priority areas for improving prognosis.Note 1 Examined over time, and in conjunction with incidence and mortality trends, survival estimates can be used to monitor progress in cancer control.Note 2 Because of the importance of cancer survival, the Canadian Cancer Registry (CCR) regularly produces survival estimates using the cohort approach. Key aspects of the methodology employed are detailed below.

Survival analyses include all primary cancers, including multiple primaries for the same person. This approach is becoming standard practice.Note 3-5 However, cancers diagnosed through autopsy only or death certificate only (DCO) are excluded from survival analysis because the date of diagnosis, and thus survival time, is unknown. Since the “true” survival of cases registered as DCO is generally poorer than those registered by other means, the common approach of excluding DCOs may bias survival estimates upward, particularly in provinces/territories with proportionally more DCOs. The magnitude of such bias, however, is generally minor.Note 6

The vital status of a person with cancer is determined through linkage with the Canadian Vital Statistics Death Database and information reported by provincial/territorial cancer registries (PTCRs). Deaths reported by PTCRs but not confirmed by linkage are included in survival analyses using the date of death submitted by PTCRs. Survival time is calculated as the number of days between the date of diagnosis and date of death or date of last follow-up (whichever is earliest). For the small percentage of persons missing month and/or day of diagnosis or death, the survival time is estimatedNote 7; however, decedents with an unknown year of death are excluded from survival analyses.

Survival analyses are performed using publicly available SAS programs to which minor adaptations are made.Note 8 The standard five-year observation time for each individual is split into multiple observations, one for each interval of follow-up time. Three month intervals are used for the first year of follow-up and six month intervals for the remaining four years for a total of 12 intervals. Since the employed actuarial life table method assumes deaths are evenly distributed within an interval, more intervals are used in the first year of follow-up because mortality is often highest and most unevenly distributed during the first year after a cancer diagnosis. With the exception of cases previously excluded because they were diagnosed through autopsy only or DCO, persons with the same date of diagnosis and death are assigned one day of survival because the SAS program automatically excludes cases with zero days of survival. Survival estimates are then calculated at discrete points in follow-up by taking the product of the interval-specific (conditional) survival estimates within the follow-up period.

Expected survival proportions are derived from sex- and province/territory-specific annual life tables by applying the Ederer II approach.Note 9 Due to small populations, only abridged life tables are produced for Prince Edward Island and the three territories. Using methods suggested by Dickman et al.Note 10, abridged life tables are expanded to complete life tables using the abridged and complete life tables for Canada. Since abridged life tables only extend to age 99 years, expected survival proportions for age 100 to 109 years are drawn from complete Canadian life tables.

Five-year observed survival is the percentage of people surviving five-years after cancer diagnosis. Five-year relative survival ratios are estimated as the ratio of the observed survival of the group diagnosed with cancer to the expected survival for the corresponding general population of the same age, sex, province of residence, and time period. In theory, relative survival ratios greater than 100% indicate that the observed survival of people with cancer is better than that expected in a comparable group from the general population. In these instances, it could be that the persons diagnosed with cancer experienced lower mortality from other causes of death because of a greater than usual interaction with the healthcare system. However, estimates of relative survival greater than 100% should be interpreted with caution as several other factors may be at play including random variation in the observed number of deaths, failure to register some cancer deaths, and imprecision in the estimation of expected survival.

As an indication of the level of statistical uncertainty in survival estimates, confidence intervals formed from standard errors estimated using Greenwood's methodNote 11 are provided. To avoid implausible lower limits less than zero and/or upper limits greater than one for observed survival estimates, asymmetric confidence intervals based on the log (-log) transformation are constructed. Relative survival ratio confidence limits are then derived by dividing the observed survival limits by the corresponding expected survival proportion.

Because survival estimates vary with age and the age distribution of cancer cases can vary over time and between geographic areas, it is usually preferable to use age-standardized survival estimates to compare survival over time, across provinces, or between a province and Canada as a whole. Age-standardized survival estimates are interpretable as the survival estimate that would have occurred if the age distribution of the cancer group under study had been the same as that of the standard population. Age-standardized estimates are calculated using the direct method. Specifically, age-specific survival estimates for a given cancer are weighted to the age distribution of persons diagnosed with that cancer over a recent, relatively long period with the age categories used in the weighting being dependent on the cancer under study. Such an approach has the advantage of producing age-standardized survival estimates that are similar to non-standardized estimates.Note 12 Specifics regarding the standard population used and age categories employed are generally detailed in the various publications released by Statistics Canada. Confidence intervals for age-standardized relative survival ratios are formed by multiplying the corresponding age-standardized observed survival lower and upper limits by the ratio of the age-standardized relative survival ratio to the age-standardized observed survival.

Notes

Mathematical Statistics (MA) — Recruitment and development program

Recruitment - Mathematical Statisticians

The Mathematical Statisticians group is not launching a recruitment campaign at this time. Future opportunities will be shared on our website. We encourage you to visit our page for updates or sign up for email notifications through jobs.gc.ca.

Consult the links below for general information about the position and the application process.

The work of a Mathematical Statistician

The work of a Mathematical Statistician

At Statistics Canada, we produce and interpret a high volume of statistical information. We sample, collect, acquire, clean, correct, combine and analyze data to explain statistical information related to many aspects of Canada's economy and society. We produce statistics by conducting censuses every five years and by conducting numerous surveys, but also by exploiting data coming from a very broad range of data sources. We develop and use innovative solutions including machine learning and big data, state-of-the-art statistical theories and leading-edge statistical methods.

Statistics Canada is currently undertaking a significant transformation. Outcomes of this transformation will be an agency that is responsive to emerging data needs, increases the statistical literacy of Canadians and facilitates the responsible use of data for decision making. Innovative statistical methods are now more than ever essential to our success. A very knowledgeable, talented and diversified workforce is at the core of this transformation and Mathematical Statisticians play a key role.

Mathematical Statisticians apply, adapt and develop mathematical, statistical or survey methods to practical problems. They explore and adopt sophisticated methods to integrate and transform alternate data sources into statistical information. Their work is crucial to Statistics Canada. The quality of data outputs and the costs of operations are heavily dependent on the methodology used.

As a mathematical statistician, your main duties will consist of designing, implementing and evaluating statistical methods related to the production of official statistics. This could include work on surveys, work on research projects in various areas related to statistical methods, or work on new methods such as integrating data from a variety of existing sources or adopting new methods to analyze data. Mathematical Statisticians can also be involved in projects related to the combination of classic and leading edge statistical methods, including experimentation with machine learning, artificial intelligence techniques, non-probabilistic sampling, micro simulation and modeled/synthetic data. Mathematical Statisticians face a wide range of theoretical and practical statistical challenges!

Statistics Canada projects are normally developed through multidisciplinary project teams. Such teams can include experts from various area: subject-matter (e.g., economists, sociologists, geographers), survey operations, systems development and methodology (mathematical statisticians). This structure requires mathematical statisticians to acquire some knowledge of the client area in order to determine and meet its methodological needs.

Within a team, the Mathematical Statistician brings his or her expertise, experience and a critical, analytical mind to the area of statistical and survey methods. In the multidisciplinary project structure, he or she is primarily a service provider. The work of a Mathematical Statistician is highly diversified and requires creativity and adaptability. Individual Mathematical Statisticians usually work on several projects or activities at the same time. Each project is a new challenge; ready-made solutions in the literature can rarely be directly applied. To design and implement effective, scientifically sound methodology, a Mathematical Statistician must always maintain a good balance of skills in analytical and empirical research and operational work. The majority of Mathematical Statisticians provide methodological support services while some of them are also involved in research.

Research

Like any organization striving to be the best in its field, Statistics Canada places great emphasis on research. The organization has a long and rich tradition of research in the area of statistical methods. In particular, methodological research focuses on cutting-edge ways to produce reliable statistics at a lower cost.

Statistics Canada provides the environment and support that enable Mathematical Statisticians to deal with all types of research problems, whether they are associated with a specific project, or are more general in nature.

Mathematical Statisticians regularly conduct theoretical studies and empirical simulations to support the methodological services they provide to project teams. They also carry out research on a variety of subjects related to statistical methods, such as spatial and temporal estimation, non-sampling variance, outlier detection, benchmarking, interpolation and calendarization, longitudinal data analysis, and time series. Initially, research could make up only a small part of the duties of a mathematical statistician. However, it could become a major part of his/her duties depending on his/her experience and interests.

Results of mathematical statisticians' research projects may be presented at relevant conferences and published in technical journals. One of these is Statistics Canada's own internationally renowned journal, Survey Methodology.

To foster and promote research, Statistics Canada has established an external fellowship program. In addition, Statistics Canada is actively involved in joint research projects with universities and with statistical agencies in other countries.

Work environment

As a new employee, you will work closely with a more experienced Mathematical Statistician which will allow you to gain valuable experience that will enhance your professional skills.

Statistics Canada is committed to offering its employees a modern and flexible workplace. A great importance is placed on the well-being of employees. We have numerous programs and facilities designed for the benefit of employees. Health and safety, respect and fairness, flexible work arrangements, a sense of belonging and recognition and workplace wellness are at the heart of our organizational culture.

Training and development

Training and development

Statistics Canada gives high priority to human resource training and development. Employees are encouraged to develop their interests and are supported throughout their career. Statistics Canada offers a complete, well-organized development program in both official languages.

Our statistical training program is large, varied and includes courses or other learning activities of high quality. In the current modernization context at Statistics Canada, mathematical-statisticians must maintain and develop their capacities related to traditional survey methods, while making room for leading-edge methods, data integration and data science.

One of the goals of our training and development program is to build a culture of productive learning. The courses in the classic classroom format are only one element among many of our training tools, that also include self-directed, informal, and hands on training.

In-house courses

A number of courses on statistics and survey methodology are offered on a regular basis by guest instructors or experienced Statistics Canada employees. The courses cover both classical theory and the results of recent research. To provide technical and professional support, a complete range of courses is also offered on other subjects as varied as informatics, project management, employee supervision and presentation skills.

All new employees also participate in a two-week, full-time course called Survey Skills Exploration Course. Participants work in teams to design a sample survey on a predetermined socio-economic topic thereby increasing their awareness of the policies, principles, complexities, and interrelationships inherent in the design of a statistical survey. This practical training is complemented by classroom sessions that provide additional knowledge on survey methods and procedures.

Seminars, Conferences, and Publications

Mathematical statisticians are encouraged to present the results of their work at seminars and at relevant conferences, and to submit articles to technical journals. In addition to publishing the journal Survey Methodology, Statistics Canada holds an annual symposium on a topical theme related to statistical methods.

University education

Statistics Canada encourages employees to continue their professional development by taking academic courses relevant to their job. Three universities in the Ottawa-Gatineau area allow employees to improve their knowledge. As well as regular courses offered by local universities, there are programs customized for Statistics Canada personnel. Furthermore, on occasion, Statistics Canada grants education leave to employees. These employees have the possibility of full-time education leave to pursue an additional university degree in statistics or a related field.

Pay rates

Pay rates

Generally speaking, all candidates are hired at the MA -2 level. The starting salary of a mathematical statistician is $67,476Footnote *. After 16 to 24 months experience at Statistics Canada, the salary reaches the first step of the MA-3 level. Annual pay increments then take place within the MA-3 level until the maximum salary is reached.

MA pay rates Footnote *
Level Position Promotion Pay rate
MA-2 MethodologistFootnote 1 Recruitment $67,476 to $80,814
MA-3 Methodologist PromotedFootnote 2 from MA-2 typically after 16 to 24 months $82,148 to $96,779
MA-4 Senior Methodologist Selection process $98,091 to $114,403
MA-5 Senior Methodologist Selection process $114,914 to $130,485
MA-6 Section Chief Selection process $128,014 to $144,531
MA-7 Assistant Director Selection process $140,171 to $156,872
Footnote *

Effective October 1st, 2024.

Return to footnote * referrer

Footnote 1

Mathematical statisticians are called 'methodologists' at Statistics Canada.

Return to first footnote 1 referrer

Footnote 2

These promotions are based on performance evaluation.

Return to first footnote 2 referrer

A registered pension plan, a dental care plan, a health care plan, a disability insurance plan, and life insurance are included in the benefits of the employees of the federal public service. As a new employee, you are entitled every year to 20 days of vacation leave, 15 days of sick leave, 5 days of leave for family-related responsibilities and 2 days of leave for a personal reason. Maternity/parental leave and up to 5 years of leave without pay for childcare and eldercare are also available.

Who can apply

Who can apply

Persons residing in Canada and Canadian citizens residing abroad. Preference will be given to veterans, Canadian citizens and permanent residents.

Application process

Application process

Step 1: Applications are online through the Public Service Commission website (Government of Canada jobs).

  • Provide the following information:
    • your résumé;
    • your grades for courses already taken at a recognized post-secondary institution (with complete codes and titles);
    • a list of courses that you are taking or will be taking at a recognized post-secondary institution during this academic year (with complete codes and titles).

Step 2: Write the test.

Step 3: Successful candidates will be invited to an interview.

Upon request, you must be able to provide the following documents:

  • a copy of your official transcripts from recognized post-secondary institutions;
  • proof of Canadian equivalency if you have a foreign degree or degrees.
Qualifications and other requirements

Qualifications and other requirements

Candidates must be able to demonstrate the following:

  • A degree from a recognized post-secondary institution with specialization in:
    1. mathematics, statistics or operational research or
    2. one of the physical, life or social sciences, combined with an acceptable number of courses (normally 15 one-term courses/ approximately 45 credits) in mathematics, statistics or operational research at the level of a recognized post-secondary institution.
  • Application of mathematical or statistical theories and techniques (including but not limited to probability theory and the distribution of random variables, hypothesis testing, analysis of variance, regression analysis, data analysis).
  • Application of mathematical, statistical or survey methods and concepts (including but not limited to questionnaire design, sample design, estimation).
  • Demonstrating integrity and respect (acting with transparency and fairness).
  • Thinking things through (exercising sound judgment and obtaining relevant facts before making decisions).
  • Working effectively with others (understanding their colleagues' roles, responsibilities and workloads, and balancing their own needs with those of other team members).
  • Showing initiative and being action-oriented (accepting responsibilities and putting forward ideas and opinions).
  • Ability to communicate effectively in writing in English or French.
Frequently asked questions

Frequently asked questions

Visit our Frequently asked questions.

Suggested readings

Suggested readings

In English

  • Cochran, W.G. (1977), Sampling Techniques, John Wiley & Sons
  • Govindarajulu, Z. (1999), Elements of Sampling Theory and Methods, Prentice Hall
  • Hansen, M., Hurwitz, W. and Madow, W. (1953), Sample Survey Methods and Theory, John Wiley and Sons
  • Kish, L. (1965), Survey Sampling, John Wiley & Sons
  • Levy, P.S. and Lemeshow, S. (1999), Sampling of Populations: Methods and Applications, John Wiley & Sons
  • Lohr, S.L. (1999), Sampling : Design and Analysis, Duxbury Press
  • Raj, D. and Chandhok, P. (1998), Sample Survey Theory, Narosa Publishing House
  • Rao, P.S.R.S. (2000), Sampling Methodologies With Applications, Chapman and Hall
  • Sarndal, C.E., Swensson, B. and Wretman, J. (1992), Model-Assisted Survey Sampling, Springer-Verlag
  • Satin, A. & Shastry, W. (1993), Survey Sampling: A Non-mathematical guide, 2nd edition, Statistics Canada, catalogue no . 12-602E
  • Statistics Canada (2003), Survey methods and practices, Statistics Canada, catalogue no . 12-587-XPE
  • Thompson, M.E. (1997), Theory of Sample Surveys, Chapman and Hall
  • Thompson, S.K. (1992), Sampling, John Wiley & Sons

In French

  • Ardilly, P. (1994), Les techniques de Sondage, Technip
  • Brossier, G. et Dussaix, A.-M. éd . (1999), Enquêtes et sondages, Méthodes, modèles, applications, nouvelles approches, Dunod
  • Morin, H. (1992) Théorie de l'échantillonnage, Les Presses de l'Université Laval
  • Satin, A. & Shastry, W. (1993), L'échantillonnage - Un guide non mathématique, 2ième édition, Statistique Canada, 12-602F au catalogue.
  • Statistique Canada (2003), Méthodes et pratiques d'enquête, Statistique Canada, 12-587-XPF au catalogue.
  • Tillé, Y. (2001), Théorie des sondages, Échantillonnage et estimation en populations finies, Dunod
Examples of questions for the written test for Mathematical Statisticians

Examples of questions for the written test for Mathematical Statisticians

The written test is evaluating knowledge AND ability to communicate in writing. It consists of two parts. Part A contains one question to test writing ability. Part B tests knowledge and contains multiple choice questions, fill-in-the-blank questions and an open question. There is no break period between the two parts of the test.

Examples of questions similar to those found on the test are given below.

Please note that tests from previous years are not available.

Part A - Writing Ability

Example 1
Prepare a letter of approximately 200 to 300 words to the director of recruitment for Statistics Canada in which you explain how your training, work experience and interpersonal skills make you a strong candidate for a position as a mathematical statistician.

Example 2
In 2002 and 2007, public health officials conducted a survey on the lifestyle choices of members of your community. The following table shows an extract of the official results of that survey:

Survey on the lifestyle choices of members of your community
Year Population (Number of Adults) Estimated number of "smoking" adults Estimated number of adults with "hypertension" Estimated number of "smoking adults with "hypertension"
2007 5,000 300 350 250
2002 4,000 400 400 200

As a journalist involved in community affairs, you have followed this story closely from the beginning. Therefore, your editor-in-chief has asked you to write an article for your newspaper which explains the survey results to your readers.

Please write this article in 200 to 300 words.

Part B - Knowledge

Probability and Statistics

1. In a batch of 10 items, we wish to extract a sample of 3 without replacement. How many different samples can we extract?

Answer: 10! / (7!*3!) = 10*9*8 / (3*2*1) = 120

2. The difference between the parameter we wish to estimate and the expected value of its estimator is __________.

Answer: the bias

3. Let X and Y be independent random variables. Suppose the respective expected values are E(X) = 8 and E(Y) = 3 and the respective variances are V(X) = 9 and V(Y) = 6. Let Z be defined as Z = 2X – 3Y +5. Based on these data, the value of E(Z) is _____ and the value of V(Z) is _____.

Answer: 12 and 90

4. Which of the following statements about the X2 (Chi-square) distribution is always false?

  1. The X2 distribution is asymmetrical.
  2. The variance of a random variable having a X2 distribution is twice its mean.
  3. If X1 and X2 are two independent random variables with a X2 distribution with n1 and n2 degrees of freedom respectively, then the variable Y = X1 + X2 has an F (Fisher) distribution with n1 and n2 degrees of freedom.
  4. If X1 , …, Xn are independent random variables having a normal distribution N(0,1), then X12 +…+ Xn2 has a X2 distribution with n degrees of freedom.
  5. The X2 distribution is dependent only on a single parameter.

Answer: C

Sampling

5. Single stage cluster sampling is more precise than simple random sampling when the ___________ is negative.

Answer: intra-cluster correlation

6. In order to estimate the total for a variable of interest, a simple random sample without replacement of size N/4 from a population of size N is sought. After some thought, it is decided that a simple random sample without replacement of size N/2, instead, will be drawn from the same population. By what factor is the variance of this estimate reduced with this increased sample size?

Answer: 3

Mathematics

7. The inverse of the matrix X = 5 2 5 4 - 1 is ___________.

Answer: X - 1 = 1 5 1 22 5 22 2 11 - 1 11 or X - 1 = 1 110 1 22 2 55 - 1 55

Data Analysis

8. The primary goal of principal component analysis is to:

  1. Divide a set of multivariate observations into classes.
  2. Assign a particular multivariate observation to one of several classes.
  3. Characterize the correlation structure between two sets of variables by replacing them by two smaller sets of variables which are highly correlated.
  4. Find the variables among a set of predictor variables that are the best predictors of a set of variables of interest.
  5. Explain the variability in a large set of variables by replacing it by a smaller set of transformed variables that explains a large portion of the total variability.

Answer: E

Open Question

9. A basic question in planning a sample survey is the size of the sample that is required. In your opinion, what factors should be considered when determining the size of the sample and how does each one affect the sample size?

Testimonials

Testimonials

"Statistics Canada is a warm, supportive workplace where you can learn and grow as a data science professional. Through the wide range of projects and available training, there are many opportunities to develop and apply data science and machine learning methods."

Angela Wang-Lin, BMath, University of Waterloo
MA-02, 2021 recruit

"Statistics Canada has a wonderful workplace culture that has allowed me to develop my skills as a methodologist in a dynamic and welcoming atmosphere. The people at Statistics Canada challenge and support each other as producers of quality information, lifelong learners and dedicated professionals."

Patricia Judd, MSc, Memorial University of Newfoundland
MA-03, 2016 recruit

"At Statistics Canada, my projects allow me to work on many steps of the survey process using state-of-the-art statistical methods. Furthermore, it's easy to achieve a balance between my work and my personal life. I have access to flexible hours which gives me the opportunity to participate in various activities outside of work."

Émilie Mayer, BSc, Laurentian University
MA-04, 2014 recruit

"I've always had varied interests and skills: should I become an author, teacher or mathematician? I discovered that I could do all of that at StatCan, and even more! Not only have I become an expert in implementing the Bootstrap in surveys, but I also provide training on related technical subjects both at the Agency and externally."

Claude Girard, MSc, Université du Québec
MA-05, 1998 recruit

"I love my job at Statistics Canada! I have the opportunity to work with really knowledgeable peers on a variety of interesting and innovative projects. And all this while continuing my training in statistics and enjoying a great work life balance!"

Matei Mireuta, PhD, McGill University
MA-05, 2016 recruit

"Working at Statistics Canada meets all my needs: I use what I have studied to work directly for the interest of Canadians and society, in a pleasant and healthy work environment. In addition, I can pursue research and international collaboration initiatives, which has allowed me to participate in numerous conferences and to win the International Association for Official Statistics prize for young statisticians in 2020."

Kenza Sallier, MSc, Université de Montréal
MA-05, 2017 recruit

"I was glad to find a job that allows me to use all my skills acquired through my years in university. Innovative projects, excellent working conditions, plenty of opportunities for advancement… All this and I get to work with a dynamic group of people! I could not ask for better."

Chi Wai Yeung, BSc, University of British Columbia
MA-05, 2005 recruit

"I enjoy very much the research and development aspects of my daily work that allow me to apply skills learned in university to prominent and innovative projects. Statistics Canada is an employer that also promotes wellness and active living at the workplace. I just love to come to work every day!"

Shuai Zhang, PhD, University of Alberta
MA-05, 2013 recruit

"As a mathematical statistician, I have daily opportunities to work on diverse statistical challenges, both theoretical and applied, alongside many talented individuals. As a working mother, Statistics Canada allows me the flexibility to raise my family while continuing to research new and exciting areas of statistics, all while connecting with statistical colleagues around the world."

Karelyn Davis, PhD, Carleton University
MA-06, 2006 recruit

"The training offered at Statistics Canada has allowed me to keep learning since my first day on the job — in a wide range of areas including my second language and supervising skills as well as statistics and computer programming."

Steven Thomas, BSc, Memorial University of Newfoundland
MA-06, 1997 recruit

"The MA stream at Statistics Canada has given me not just a job, but a career. From junior to senior, I have been able to choose my path and work on projects that both interest and challenge me. I feel Statistics Canada has really invested in my development, even while starting a family."

Beatrice Baribeau, BMath, University of Waterloo
MA-07, 2004 recruit

Contact our recruitment team

Contact our recruitment team

Note that if you require help with the on-line application process, you must contact the Public Service Commission of Canada at 1-888-780-4444.

Contact us at statcan.marecruitment-marecrutement.statcan@statcan.gc.ca.

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Quarterly financial reports outlining results, risks and significant changes in operations, personnel and program.

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Information about the fees that Statistics Canada had the authority to set for services, licences, permits, products, the use of facilities, and other items.

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Description for Chart 1: Comparison of gross budgetary authorities and expenditures as of June 30, 2013, and June 30, 2014, in thousands of dollars

This bar graph shows Statistics Canada's budgetary authorities and expenditures, in thousands of dollars, as of June 30, 2013 and 2014:

  • As at June 30, 2013
    • Net budgetary authorities: $400,509
    • Vote netting authority: $120,000
    • Total authority: $520,509
    • Net expenditures for the period ending June 30: $124,232
    • Year-to-date revenues spent from vote netting authority for the period ending June 30: $15,063
    • Total expenditures: $139,295
  • As at June 30, 2014
    • Net budgetary authorities: $379,555
    • Vote netting authority: $120,000
    • Total authority: $499,555
    • Net expenditures for the period ending June 30: $121,613
    • Year-to-date revenues spent from vote netting authority for the period ending June 30: $12,951
    • Total expenditures: $134,564
 
 

Statement outlining results, risks and significant changes in operations, personnel and program

A) Introduction

Statistics Canada's mandate

Statistics Canada is a member of the Industry portfolio.

Statistics Canada's role is to ensure that Canadians have access to a trusted source of statistics on Canada that meets their highest priority needs.

The Agency's mandate derives primarily from the Statistics Act. The Act requires that the Agency collects, compiles, analyzes and publishes statistical information on the economic, social, and general conditions of the country and its people. It also requires that Statistics Canada conduct the census of population and the census of agriculture every fifth year, and protects the confidentiality of the information with which it is entrusted.

Statistics Canada also has a mandate to co-ordinate and lead the national statistical system. The Agency is considered a leader, among statistical agencies around the world, in co-ordinating statistical activities to reduce duplication and reporting burden.

More information on Statistics Canada's mandate, roles, responsibilities and programs can be found in the 2014–2015 Main Estimates and in the Statistics Canada 2014–2015 Report on Plans and Priorities.

The quarterly financial report

Statistics Canada has the authority to collect and spend revenue from other government departments and agencies, as well as from external clients, for statistical services and products.

Basis of presentation

This quarterly report has been prepared by management using an expenditure basis of accounting. The accompanying Statement of Authorities includes the Agency's spending authorities granted by Parliament and those used by the Agency consistent with the Main Estimates for the 2014–2015 fiscal year. This quarterly report has been prepared using a special purpose financial reporting framework designed to meet financial information needs with respect to the use of spending authorities.

The authority of Parliament is required before moneys can be spent by the Government. Approvals are given in the form of annually approved limits through appropriation acts or through legislation in the form of statutory spending authority for specific purposes.

The Agency uses the full accrual method of accounting to prepare and present its annual departmental financial statements that are part of the departmental performance reporting process. However, the spending authorities voted by Parliament remain on an expenditure basis.

B) Highlights of fiscal quarter and fiscal year-to-date results

This section highlights the significant items that contributed to the net decrease in resources available for the year, as well as actual expenditures for the quarter ended June 30.

Description for Chart 1

Outlines the gross budgetary authorities, which represent the resources available for use for the year as of June 30.

Chart 1 outlines the gross budgetary authorities, which represent the resources available for use for the year as of June 30.

Significant changes to authorities

Total authorities available for 2014–2015 have decreased by $20.9 million, or 4%, from the previous year, from $520.5 million to $499.6 million (Chart 1). This net decrease was mostly the result of the following:

  • decrease for the 2011 Census of Population and the National Household Survey ($6.2 million) and the 2011 Census of Agriculture ($1.8 million), as the programs wind down;
  • net reductions related to Budget 2012 saving measures ($15.6 million);
  • decrease for the transfer of funds to Shared Services Canada for workplace technology device software ($1.6 million);
  • partially offset by an economic increase for collective agreements ($5 million).

In addition to the appropriations allocated to the Agency through the Main Estimates, Statistics Canada also has vote net authority within Vote 105, which entitles the Agency to spend revenues collected from other government departments, agencies, and external clients to provide statistical services. Vote netting authority is stable at $120 million in each of the fiscal years 2013–2014 and 2014–2015.

Significant changes to expenditures

Year-to-date net expenditures recorded to the end of the first quarter decreased by $2.6 million, or 2%, from $124.2 million to $121.6 million. (See Table A: Variation in Departmental Expenditures by Standard Object.)

Statistics Canada spent approximately 27% of its authorities by the end of the first quarter, compared with 27% in the same quarter of 2013–2014.

Table A: Variation in Departmental Expenditures by Standard Object (unaudited)
This table displays the variance of departmental expenditures by standard object between fiscal 2013-2014 and 2014-2015. The variance is calculated for year to date expenditures as at the end of the first quarter. The row headers provide information by standard object. The column headers provide information in thousands of dollars and percentage variance for the year to date variation.
Departmental Expenditures Variation by Standard Object Q1 year-to-date variation
$'000 %
(01) Personnel -18,130 -13.9
(02) Transportation and communications -316 -13.2
(03) Information 53 76.8
(04) Professional and special services 1,150 62.1
(05) Rentals 1,178 52.4
(06) Repair and maintenance 45 136.4
(07) Utilities, materials and supplies -98 -20.9
(08) Acquisition of land, buildings and works - -
(09) Acquisition of machinery and equipment -2,011 -91.5
(10) Transfer payments - -
(12) Other subsidies and payments 13,398 267,960.0
Total gross budgetary expenditures -4,731 -3.4
Less revenues netted against expenditures
Revenues -2,112 -14.0
Total net budgetary expenditures -2,619 -2.1

01) Personnel: The decrease resulted from incurring expenditures for severance liquidations related to the signing of collective agreements in the first quarter of 2013–2014. These expenditures were partly offset by increased salary expenditures, resulting from annual increments and the signing of collective bargaining agreements.

04) Professional and special services: The increase resulted from increased spending on informatics services.

05) Rentals: The increase resulted from increased maintenance costs associated with additional database hosting licenses acquired.

09) Acquisition of machinery and equipment: The decrease resulted from acquiring computer equipment in the first quarter of 2013–2014.

12) Other subsidies and payments: The increase resulted from a one-time transition payment for implementing salary payment in arrears by the Government of Canada.

The decrease in revenues resulted primarily from timing differences between years for the receipt of funds and scheduled key deliverables.

C) Risks and uncertainties

In 2014–2015, Statistics Canada plans to continue monitoring budget pressures, including the cost-saving measures announced in Budget 2014, with the following actions and mitigation strategies:

  • additional analysis, monitoring and validation of financial and human resources information through a modified monthly financial package for budget holders
  • review of monthly project dashboards in place across the Agency to monitor project issues, risks and alignment with approved budgets
  • continued realignment and reprioritization of work

In addition, Statistics Canada uses risk management and a risk-based decision-making process to prioritize and conduct its business. To do so effectively, the Agency identifies its key risks and develops corresponding mitigation strategies in its Corporate Risk Profile.

D) Significant changes to operations, personnel and programs

No significant changes in relation to operations, personnel and programs have occurred over the last quarter.

E) Budget 2012 implementation

This section provides an overview of the savings measures announced in Budget 2012 that are being implemented in order to refocus government and programs, make it easier for Canadians and businesses to deal with their government, as well as modernize and reduce the back office.

Statistics Canada's savings target as announced in Budget 2012 Economic Action Plan is $33.9 million by 2014–2015. This reduction is being implemented progressively, beginning with $8.3 million on April 1, 2012, rising to $18.3 million on April 1, 2013, in order to achieve the full reduction by April 1, 2014. The reductions, as of April 1, 2014, have been reflected in Statistics Canada's Main Estimates. To meet this target, Statistics Canada has focused resources where they are most needed.

The savings incurred through these program adjustments represent moderate reductions in the production of statistics to support development, administration, and evaluation of policy, while continuing to meet the public's highest priority needs. In some cases, the information will continue to be available in a different format. A full list of program adjustments is available online.

There are no financial risks or uncertainties related to these reductions.

Approval by senior officials

The original version was signed by
Wayne R. Smith, Chief Statistician
Stéphane Dufour, Chief Financial Officer
Date signed August 21, 2014

Departmental budgetary expenditures by Standard Object (unaudited) - Fiscal year 2014-2015
This table displays the departmental expenditures by standard object for the fiscal year 2014-2015. The row headers provide information by standard object for expenditures and revenues. The column headers provide information in thousands of dollars for planned expenditures for the year ending March 31; expended during the quarter ended June 30; and year to date used at quarter-end 2014-2015.
  Fiscal year 2014-2015
Planned expenditures for the year ending March 31, 2015 Expended during the quarter ended June 30, 2014 Year to date used at quarter-end
in thousands of dollars
Expenditures
(01) Personnel 401,121 111,901 111,901
(02) Transportation and communications 25,808 2,075 2,075
(03) Information 2,509 122 122
(04) Professional and special services 35,680 3,001 3,001
(05) Rentals 13,154 3,426 3,426
(06) Repair and maintenance 7,044 78 78
(07) Utilities, materials and supplies 13,241 370 370
(08) Acquisition of land, buildings and works - - -
(09) Acquisition of machinery and equipment 825 188 188
(10) Transfer payments - - -
(12) Other subsidies and payments 173 13,403 13,403
Total gross budgetary expenditures 499,555 134,564 134,564
Less revenues netted against expenditures
Revenues 120,000 12,951 12,951
Total revenues netted against expenditures 120,000 12,951 12,951
Total net budgetary expenditures 379,555 121,613 121,613
Departmental budgetary expenditures by Standard Object (unaudited) - Fiscal year 2013-2014
This table displays the departmental expenditures by standard object for the fiscal year 2013-2014. The row headers provide information by standard object for expenditures and revenues. The column headers provide information in thousands of dollars for planned expenditures for the year ending March 31; expended during the quarter ended June 30; and year to date used at quarter-end 2013-2014.
  Fiscal year 2013-2014
Planned expenditures for the year ending March 31, 2014 Expended during the quarter ended June 30, 2013 Year-to-date used at quarter-end
in thousands of dollars
Expenditures
(01) Personnel 419,449 130,031 130,031
(02) Transportation and communications 26,173 2,391 2,391
(03) Information 2,656 69 69
(04) Professional and special services 33,940 1,851 1,851
(05) Rentals 9,224 2,248 2,248
(06) Repair and maintenance 11,951 33 33
(07) Utilities, materials and supplies 12,355 468 468
(08) Acquisition of land, buildings and works - - -
(09) Acquisition of machinery and equipment 4,586 2,199 2,199
(10) Transfer payments - - -
(12) Other subsidies and payments 175 5 5
Total gross budgetary expenditures 520,509 139,295 139,295
Less revenues netted against expenditures
Revenues 120,000 15,063 15,063
Total revenues netted against expenditures 120,000 15,063 15,063
Total net budgetary expenditures 400,509 124,232 124,232
Statement of Authorities (unaudited) - Fiscal year 2014-2015
This table displays the departmental authorities for the fiscal year 2014-2015. The row headers provide information by type of authority, Vote 105 – Net operating expenditures, Statutory authority and Total Budgetary authorities. The column headers provide information in thousands of dollars for Total available for use for the year ending March 31; used during the quarter ended June 30; and year to date used at quarter-end for 2014-2015.
  Fiscal year 2014-2015
Total available for use for the year ending March 31, 2015* Used during the quarter ended June 30, 2014 Year to date used at quarter-end
in thousands of dollars
Vote 105 – Net operating expenditures 322,744 107,410 107,410
Statutory authority – Contribution to employee benefit plans 56,811 14,203 14,203
Total budgetary authorities 379,555 121,613 121,613
Statement of Authorities (unaudited) - Fiscal year 2013-2014
This table displays the departmental authorities for the fiscal year 2013-2014. The row headers provide information by type of authority, Vote 105 – Net operating expenditures, Statutory authority and Total Budgetary authorities. The column headers provide information in thousands of dollars for Total available for use for the year ending March 31; Used during the quarter ended June 30; and year to date used at quarter-end for 2013-2014.
  Fiscal year 2013-2014
Total available for use for the year ended March 31, 2014* Used during the quarter ended June 30, 2013 Year to date used at quarter-end
in thousands of dollars
Vote 105 – Net operating expenditures 338,342 108,690 108,690
Statutory authority – Contribution to employee benefit plans 62,167 15,542 15,542
Total budgetary authorities 400,509 124,232 124,232