Data Analiysis

Data Analiysis

• Scan existing indices and databases to identify accessible sources of data;
• Choose main topics to be assessed in the urban prosperity index, argue why the topics are important to the urban quality of life, and whether and why different topics should be weighted differently;
• Identify indicators that attempt to measure the topics they want included in the index, argue how the indicators relate to the topic, and cite where data originate so to be comparable across cities and repopulated periodically;
• Build an index that will score and rank at least five cities from different regions of Canada or the world;
• Discuss the limitations of specific proxy variables, as well as indices generally, in understanding urban issues and their quality of life.

What are indices?
Indices are models built with weighted indicators, enabling the scoring and ranking of subjects (in our case cities) according to pre-determined priorities.
• Indicators: data that measure (or proxy) a variable
• Weights: a factor by which an indicator is multiplied to reflect relative importance

Key features of a good index
• Relevancy. Indicators measure meaningful and important features
• Accuracy. Indicators approximate/proxy what is intended to be measured
• Accessibility. Data are easy to find and inexpensive to acquire
• Periodicity. Data are updated regularly.
• Comparability. Data are comparable across jurisdictions
• Scalability. Data are available for neighborhood through national levels

Table 282-0110 Labour force survey estimates (LFS), by census metropolitan area based on 2006 census boundaries, sex and age group, annual (persons unless otherwise noted)(1,2,3)
Survey or program details:
Labour Force Survey – 3701
Geography (4) Labour force characteristics Sex Age group 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Halifax, Nova Scotia [12205] Population (x 1,000) (5) Both sexes 15 years and over 302.8 306.5 309.2 313 317.5 322.7 328.7 334.3 339.2 343.4 347.5
Halifax, Nova Scotia [12205] Labour force (x 1,000) (6) Both sexes 15 years and over 209.9 215.1 214.3 215.8 222.2 223.5 234.1 236 238.3 239.7 243.2
Halifax, Nova Scotia [12205] Employment (x 1,000) (7) Both sexes 15 years and over 196.1 202.1 201.9 205 210.6 211.9 219.2 221.1 223.9 225.1 227.3
Halifax, Nova Scotia [12205] Unemployment rate (rate) (12) Both sexes 15 years and over 6.6 6 5.8 5 5.2 5.2 6.4 6.3 6 6.1 6.6
Québec, Quebec [24421] Population (x 1,000) (5) Both sexes 15 years and over 581.3 586.6 591.3 598.1 605.4 612.9 620.8 628.7 636.5 642.7 647.8
Québec, Quebec [24421] Labour force (x 1,000) (6) Both sexes 15 years and over 388.2 387 399.5 396.5 406.2 412.5 415.3 431.1 443.2 444.5 442.8
Québec, Quebec [24421] Employment (x 1,000) (7) Both sexes 15 years and over 361.2 364.8 377.3 375.6 385.6 393.8 395.1 410.2 419.7 422 421.9
Québec, Quebec [24421] Unemployment rate (rate) (12) Both sexes 15 years and over 7 5.8 5.6 5.2 5.1 4.5 4.9 4.9 5.3 5.1 4.7
Montréal, Quebec [24462] Population (x 1,000) (5) Both sexes 15 years and over 2911.4 2940.9 2972.6 3008.6 3048.2 3091.4 3137.9 3182.1 3222.4 3256.2 3292.3
Montréal, Quebec [24462] Labour force (x 1,000) (6) Both sexes 15 years and over 1989 1985.6 2000.6 2024.8 2052.4 2070.2 2097.4 2138.9 2129.4 2162.6 2209.5
Montréal, Quebec [24462] Employment (x 1,000) (7) Both sexes 15 years and over 1799.4 1814.3 1826.8 1854.6 1908.5 1917.2 1905.4 1954.2 1952.5 1978.8 2031.7
Montréal, Quebec [24462] Unemployment rate (rate) (12) Both sexes 15 years and over 9.5 8.6 8.7 8.4 7 7.4 9.2 8.6 8.3 8.5 8
Hamilton, Ontario [35537] Population (x 1,000) (5) Both sexes 15 years and over 560.4 569 576.7 581.7 588.6 596.4 603.9 611.5 618.4 624.9 631.2
Hamilton, Ontario [35537] Labour force (x 1,000) (6) Both sexes 15 years and over 383 393.6 382.8 389.5 393.9 397.5 408.2 402.5 405.3 408 402.8
Hamilton, Ontario [35537] Employment (x 1,000) (7) Both sexes 15 years and over 359.5 368.7 361.6 366.2 370.1 373.1 374.1 371.8 379.4 381.2 377.1
Hamilton, Ontario [35537] Unemployment rate (rate) (12) Both sexes 15 years and over 6.1 6.4 5.6 6 6 6.1 8.4 7.6 6.4 6.5 6.4
Footnotes:
1 The Labour force survey collection of tables, starting with number 282-, is large with many possible cross-tabulations for the 10 provinces and other geographic regions. To ensure respondent’s confidentiality, detailed data are suppressed. Data for Canada, Quebec, Ontario, Alberta and British Columbia are suppressed if the estimate is below 1,500, for Newfoundland and Labrador, Nova Scotia, New Brunswick, Manitoba and Saskatchewan, if the estimate is below 500, and for Prince Edward Island, under 200. For suppression levels within census metropolitan areas (CMAs) and economic regions (ERs), use the respective provincial suppression levels above. While suppressing to protect respondent confidentiality has the added effect of blocking-out the lowest-quality LFS data, some remaining non-suppressed data in these very large LFS CANSIM tables may be of insufficient quality to allow for accurate interpretation. Please be warned that the more detailed your LFS CANSIM download, the smaller the sample size upon which your LFS estimates will be based, and the greater the risk of downloading poorer quality data.
2 Estimates from this table are based on 2006 census population counts.
3 Estimates in this table are based on 2006 census boundaries. For comparisons before 1996, please use the concordance table in the CANSIM What’s new announcement from December 17, 2010. Note that with the change to the 2006 census boundaries, six new CMAs were added (Moncton, New Brunswick; Peterborough, Ontario; Brantford, Ontario; Barrie, Ontario; Guelph, Ontario; Kelowna, British Columbia). Also, the boundaries of seven CMAs were modified (Québec, Quebec; Sherbrooke, Quebec; Montréal, Quebec; Ottawa-Gatineau, Quebec part; Ottawa-Gatineau, Ontario/Quebec; London, Ontario; Winnipeg, Manitoba).
4 A census metropolitan area (CMA) is a large urban area (known as urban core) together with adjacent urban and rural areas (known as urban and rural fringe) that have a high degree of social and economic integration with the urban cores. A CMA has an urban core population of at least 100,000.
5 Number of persons of working age. Estimates in thousands, rounded to the nearest hundred.
6 Number of civilian, non-institutionalized persons 15 years of age and over who, during the reference week, were employed or unemployed. Estimates in thousands, rounded to the nearest hundred.
7 Number of persons who, during the reference week, worked for pay or profit, or performed unpaid family work or had a job but were not at work due to own illness or disability, personal or family responsibilities, labour dispute, vacation, or other reason. Those persons on layoff and persons whose job attachment was to a job to start at a definite date in the future are not considered employed. Estimates in thousands, rounded to the nearest hundred.
12 The unemployment rate is the number of unemployed persons expressed as a percentage of the labour force. The unemployment rate for a particular group (age, sex, marital status) is the number unemployed in that group expressed as a percentage of the labour force for that group. Estimates are percentages, rounded to the nearest tenth.
Source:
Statistics Canada. Table 282-0110 – Labour force survey estimates (LFS), by census metropolitan area based on 2006 census boundaries, sex and age group, annual (persons unless otherwise noted)
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