TableBuilder: Motor Vehicle Use, Australia

Use this data in TableBuilder to produce your own tables and graphs. Data is available in TableBuilder for 2016, 2018 and 2020.

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See Survey of Motor Vehicle Use, Australia, 12 months 30 June 2020 for summary results and collection methodology.

The Motor Vehicle Use TableBuilder product is structured as two separate datasets:

• Motor Vehicle Use, 2020 (Includes summations of Kilometres travelled, Tonnes carried, Tonne-kilometres travelled, Fuel consumed); and
• Motor Vehicle Use, 2020 - Number of vehicles (Includes summation of Number of vehicles and the variables of State/territory of registration, Vehicle type and Year of manufacture groups).

Each dataset is structured with two levels, a vehicle level and a use level.

The vehicle level contains information such as:

• state/territory of registration
• type of vehicle
• fuel type
• year of manufacture groups
• other vehicle characteristics

The use level covers types of use, including:

• area of operation
• state/territory of operation
• business use
• other types of use

The data items list in the Data downloads section is the definitive source of available data items and categories. Use the data items list to confirm the TableBuilder products fulfil the requirements for your research before purchasing your subscription.

The TableBuilder User Guide provides you with information about how to create basic tables, custom groups, graphs and large tables. It also includes practical examples and video tutorials.

Motor Vehicle Use contains a mandatory field called Total, which is from the Use Type fields contained in the Use level. By default this field is present in any new table. Due to some Use types being sub-totals, the automatic total function in this product has been turned off for Use types, with totals being generated through the mandatory field of Total.

Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfied the parameters of a particular cell in a table were in the survey. This is despite there being vehicles in the general population with those characteristics. This is an example of sampling variability which occurs with all sample surveys. Relative Standard Errors cannot be generated for zero cells.

Due to the rounding of most summations, there will be some instances of cells showing zero values that are a valid response, these are indicated by having a generated Relative Standard Error.

We don't recommend you use more than 4 variables when constructing tables. Although results will be produced, due to the level of disaggregation, estimates will have high RSEs (Relative Standard Errors) and results may be sparse.

RSEs between 25% and 50% are considered to be high and should be used with caution. Estimates with an RSE higher than 50% are considered unreliable for general use.

Some results may be sparse and produce zero values but have an associated RSE. This is because they have been rounded to the nearest unit of measurement. This can occur for Kilometres travelled (millions), Tonne-kilometres travelled (millions), Tonnes carried (thousands) and Fuel consumed (millions).

This release previously used catalogue number 9208.0.55.008.