For a brief explanation on how cohort-component methodology works, click here. It's a complex equation using illation. One important variable entails tallying the number of deaths in a fixed period. My question would be, with the exact death count being indeterminable due to the crime figures being unknown how did StatsSA arrive at the figure? The SAPS official count which is very dated (17 months) puts forward a figure of 20 000 murders per year, the medical board puts the murder rate a third higher and Interpol puts it at twice the rate. So how did they get this figure? StatsSA should be renamed ThumbsuckSA. Notice too that no mention is made of the estimated 3 - 8 million illegals either. The fact is, without a proper census, it's all bad guesswork. Useless.***
Statistics body's estimates of population by province, race and gender.
Table1: Mid-year population estimates for South Africa by population group and sex, 2009
| Population group | Male |
| Female |
| Total |
|
| Number | Percentage of total population | Number | Percentage of total population | Number | Percentage of total population | |
| African | 18,901,000 | 79.2% | 20,235,200 | 79.5% | 39,136,200 | 79.4% |
| Coloured | 2,137,300 | 9.0% | 2,295,800 | 9.0% | 4,433,100 | 9.0% |
| Indian/Asian | 635,700 | 2.7% | 643,400 | 2.5% | 1,279,100 | 2.6% |
| White | 2,194,700 | 9.2% | 2,277,400 | 8.9% | 4,472,100 | 9.1% |
|
| 23,868,700 | 100.0% | 25,451,800 | 100.0% | 49,320,500 | 100.0% |
Table 2: Mid-year population estimates by province, 2009
| Province | Number | Percentage of total population |
| Eastern Cape | 6,648,600 | 13.5% |
| Free State | 2,902,400 | 5.9% |
| Gauteng | 10,531,300 | 21.4% |
| KwaZulu-Natal | 10,449,300 | 21.2% |
| Limpopo | 5,227,200 | 10.6% |
| Mpumalanga | 3,606,800 | 7.3% |
| Northern Cape | 1,147,600 | 2.3% |
| North West | 3,450,400 | 7.0% |
| Western Cape | 5,356,900 | 10.9% |
| Total | 49,320,500 | 100.0% |
Summary
This release uses the cohort-component methodology to estimate the 2009 mid-year population of South Africa.
The estimates cover all the residents of South Africa at the 2009 mid-year, and are based on the latest available information. Estimates may change as new data become available.
For 2009, Statistics South Africa Stats SA) estimates three variants of the population. The low variant estimates the population at 48,88 million, and the high variant at 49,68 million. The medium variant of the population estimated at 49,32 million should be regarded as the best estimate of the 2009 mid-year population.
Fifty-two per cent (approximately 25,45 million) of the population is female.
Gauteng comprises the largest share of the South African population. Approximately 10,53 million people (21,4%) live in this province. KwaZulu-Natal is the province with the second largest population, with 10,45 million people (21,2%) living in this province. With a population of approximately 1,15 million people (2,3%), Northern Cape remains the province with the smallest share of the South African population.
Nearly one-third (31,4%) of the population is aged younger than 15 years and approximately 7,5% (3,7 million) is 60 years or older. Of those younger than 15 years, approximately 23% (3,54 million) live in KwaZulu-Natal and 17,9% (2,78 million) live in Gauteng.
Migration is an important demographic process in shaping the age structure and distribution of the provincial population.
For the period 2006-2011 it is estimated that approximately 390 000 people will migrate from the Eastern Cape; Limpopo is estimated to experience a net outmigration of nearly 200 000 people. During the same period, Gauteng and Western Cape are estimated to experience a net inflow of migrants of approximately 450 000 and 140 000 respectively.
Life expectancy at birth is estimated at 53,5 years for males and 57,2 years for females.
The infant mortality rate is estimated at 45,7 per 1 000 live births.
The estimated overall HIV prevalence rate is approximately 10,6%. The total number of people living with HIV is estimated at approximately 5,21 million. For adults aged 15-49 years, an estimated 17% of the population is HIV positive.
For 2009, this release estimates that approximately 1,5 million people aged 15 and older and approximately 106 000 children would be in need of ART.
The total number of new HIV infections for 2009 is estimated at 413 000. Of these, an estimated 59 000 will be among children.
Issued by Statistics South Africa, July 27 2009
4 Opinion(s):
If they don't like the way the sum function adds up, they overwrite it with their own "balancing figure". I had a black accountant trying this on me. She don't know what was wrong with this, and called me ... yep .. a racist.
..hold on, I'm going to take a shot at this....
now...where are my bones....
I think this is pertinent
1996 Census
NOTE ABOUT UNEMPLOYMENT
Statistics South Africa (Stats SA) has recently changed the official definition of unemployment, in line with 80% of other developed and developing countries. According to the new definition:
• The unemployed are those people within the economically active population who:
( a ) did not work during the seven days prior to the interview,
( b ) want to work and are available to start work within a week of the interview, and
( c ) have taken active steps to look for work or to start some form of self-employment in the four weeks prior to the interview.
• The official unemployment rate is calculated as the percentage of the economically active population which is unemployed, according to the above definition.
• The new official unemployment rate corresponds to what Stats SA previously called the strict unemployment rate, i.e. using criterion (c) as well as (a) and (b). By contrast, the expanded unemployment rate does not require criterion (c). It was the previous official definition.
In the census questionnaire, questions were not asked on work-seeking behaviour in the four weeks prior to the night of Census '96. Therefore we cannot use the new official definition in this publication to describe unemployment rates. Instead, the expanded definition will be used, and all figures and percentages in this issue are based on expanded unemployment rates.
Total = 34% unemployed
http://www.statssa.gov.za/census01/Census96/HTML/CIB/Population/230.htm
http://www.statssa.gov.za/census01/Census96/HTML/CIB/Population/219.htm
http://www.statssa.gov.za/census01/Census96/HTML/CIB/Population/234.htm
Now this is the part of these stats I don't understand
In 1996 we had 25 million between 15 and 64 years of age. 9,1 Million were officially employed = 36% employed/64% unemployed
In 2009 we have 31 million in the same age group. 13,3 million are employed = 42,9% employed/57.1% unemployed.
The first BUT. In 1996 there does not seem to be informal employment counted as employed, yet in 2009 this sector makes up 2,1 million (13,3% of those employed). So, if we take this out of employed, we get to 36% employed/64% unemployed.
I.E. comparing apples with apples = Zero gain.
Now understand that I have not broken down the reasons for unemployment, as this is where things get fudged. I simple took the two firm statistics, employment and economically active age, in order to compare.
What this means to me is that COSATU were right, we have made no gains in 15 years, but we should have, as sanctions were lifted, creating our own boom, and we had a worldwide boom.
So, what is the true picture? More importantly, 20,8% of the population is in the 10 to 19 age group, needing jobs in the next one to ten years. Only 8% will retire in the next ten years, so we will need to create an average of 700,000 jobs a year just to keep unemployment levels as they are.
Please check my numbers in case I am wrong.
Thanks for the great info Anon.
Very scary statistics indeed, and it just shows how these stats can be manipulated.
Now one has to add the 3 million Zimbabweans, 1 million Ethiopian and Somalis, and who now how many million others in the mix to get the true picture of the bright future ahead of the rainbow nation.
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