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Type of Non-Private Dwelling
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Applicable to: Non-private dwellings
01. Hotel, motel, bed and breakfast
02. Nurses' quarters
03. Staff quarters
04. Boarding house, private hotel
05. Boarding school
06. Residential college, hall of residence
07. Public hospital (not psychiatric)
08. Private hospital (not psychiatric)
09. Psychiatric hospital or institution
10. Hostel for the disabled
11. Nursing home
12. Accommodation for the retired or aged (not self-contained)
13. Hostel for homeless, night shelter, refuge
14. Childcare institution
15. Corrective institution for children
16. Other welfare institution
17. Prison, corrective institution for adults
18. Immigration detention centre
19. Convent, monastery, etc.
20. Other and not classifiable
&& Not stated
@@ Not applicable
Total number of categories: 22
More Detailed Description
Quality Statement for Type of Non-Private Dwellings (NPDD)
There are many aspects which can affect the quality of Census data; the following information should be considered when viewing data on Type of Non-Private Dwellings (NPDD).
It is becoming increasingly difficult to determine whether some dwellings are private dwellings or non-private dwellings. For example, hotels or resorts can also provide self contained and long term accommodation (features of private dwellings); retirement villages can offer a mix of communal or fully self contained accommodation. Consequently, there will be a number of such dwellings that may have been classified incorrectly as either private or as non-private dwellings.
As well as becoming difficult to determine particular classes of dwellings as either private or non-private, it is also becoming more difficult to determine the Type of Non-Private Dwelling. The numbers of dwellings in the "Other and not classifiable" category had grown significantly between 1996 and 2001 so investigations were conducted of this category during processing of 2006 data. Using other information it was found that a number could be recoded to a more specific category. This exercise helps explain the fall in this category from 13.8% of non-private dwellings in 2001 to 9.0% in 2006. Dwellings most commonly recoded were to "Hotel, motel, bed and breakfast", "Staff quarters", "Other welfare institution" and "Psychiatric hospital or institution".
For 2006, a small number of non-private dwellings were unable to be coded to Type of Non-Private Dwelling (NPDD), resulting in a non-response rate of 1.1%. In 2001 those non-private dwellings that were unable to be coded to a specific category were coded to "Other and not classifiable".
The ABS aims to produce high quality data from the Census. To achieve this, extensive effort is put into Census form design, collection procedures, and processing procedures.
There are four principal sources of error in Census data: respondent error, processing error, partial response and undercount. Quality management of the Census program aims to reduce error as much as possible, and to provide a measure of the remaining error to data users, to allow them to use the data in an informed way.
When completing their Census form, some people do not answer all the questions which apply to them. In these instances, a 'not stated' code is allocated during processing, with the exception of non-response to age, sex, marital status and place of usual residence. These variables are needed for population estimates, so they are imputed using other information on the Census form, as well as information from the previous Census.
The processing of information from Census forms is now mostly automated, using scanning, Intelligent Character Recognition and other automatic processes. Quality assurance procedures are used during Census processing to ensure processing errors are kept at an acceptable level. Sample checking is undertaken during coding operations, and corrections are made where necessary.
The Census form may be completed by one household member on behalf of others. Incorrect answers can be introduced to the Census form if the respondent does not understand the question or does not know the correct information about other household members. Many of these errors remain in the final data.
More detailed information on data quality is available in the 2006 Census Dictionary (cat. no. 2901.0), in the section titled Managing Census Quality.