4921.0.55.001 - Microdata: Cultural Activities, Australia, 2017-18 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 28/05/2019   
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For general information relating to TableBuilder and instructions on how to use features of the TableBuilder product, please refer to the Table Builder, User Guide (cat. no. 1406.0.55.005).

Specific information applicable to Cultural Activities, Australia, 2017-18 TableBuilder product is outlined below.


Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each sample unit. The weight is the value that indicates how many population units are represented by the sample unit.

As the format of the 2017-18 Cultural Activities TableBuilder files are at the person or child level, there is only one weight provided on each - a person or child weight. That is, all tables produced provide estimates of the number of people with particular characteristics. The Summation Options section in the customised Table View panel in TableBuilder contains this weight. As there is only one weight available, the person or child weight (Persons for the Adults dataset and Children for the Children dataset) will be automatically applied when producing tables.


Sampling error is a measure of the difference between published estimates, derived from a sample of persons, and the value that would have been produced if the total population (as defined by the scope of the survey) had been included in the survey.

One measure of the likely difference is given by the standard error (SE), which indicates the extent to which an estimate might have varied because only a sample of dwellings was included. There are about two chances in three (67%) that the sample estimate will differ by less than one SE from the figure that would have been obtained if all dwellings had been included, and about 19 chances in 20 (95%) that the difference will be less than two SEs.

Relative standard error (RSE) is a measure of sampling variability. The RSE is obtained by expressing the SE as a percentage of the estimate to which it is related.

Data users should note that TableBuilder automatically produces the RSE of the estimate. Users can output RSE values for a produced table by clicking on the ‘Options’ button, hovering over the ‘Relative Standard Error’ tab and selecting either ‘RSE’ or ‘Summation + RSE’. Selecting ‘RSE’ will simply display the RSEs in each cell of the table. On the other hand, selecting ‘Summation + RSE’ will show both the estimate and the RSE highlighted in red.

For more information for using RSEs in TableBuilder, refer to the Relative Standard Error page of the TableBuilder, User Guide (cat. no. 1406.0.55.005).


TableBuilder includes a number of continuous variables which can have a response value at any point along a continuum. Some continuous data items are allocated special codes for certain responses (e.g. 000 = 'Not applicable').

When creating ranges in TableBuilder for such continuous items, special codes will automatically be excluded. Therefore the total will show only 'valid responses' rather than all responses (including special codes). Continuous items with special codes have a corresponding categorical item in the Person Level Data Items that provides the ability to display data for the special code. Any special codes for continuous data items are listed in the Data Item List.

Note that there are no continuous data items for cultural attendance.


    A number of the survey's data items allow respondents to report more than one response. These are referred to as 'multiple response' data items. An example of such a data item is 'Type of cultural activity undertaken in last 12 months (multiple response)'. For this data item, respondents may have undertaken any combination of one or more of the selected activities in the last 12 months.

    When a multiple-response data item is tabulated, a person is counted against each category for which they have provided a response. Therefore the sum of the components will be more than or equal to the total population, as some persons are counted multiple times. Multiple–response data items can be identified in the Data Item List, as they include 'multiple response' in the data item label. The Data Item List can be accessed from the Downloads tab.


    Most data items include a 'Not applicable' category. The 'Not applicable' category comprises those respondents who were not asked a particular question(s) and hence are not applicable to the population to which the data item refers. The classification value of the 'Not applicable' category, where relevant, is shown in the Data Item List and can be accessed from the Downloads tab.


    To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.

    After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.

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