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9208.0 - Survey of Motor Vehicle Use, Australia, Oct 2002  
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 25/09/2003   
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TECHNICAL NOTE 1: DATA QUALITY


DATA QUALITY

When interpreting the results of a survey it is important to take into account factors that may affect the reliability of estimates. Such factors can be classified as either sampling error or non-sampling error.

SAMPLING ERROR

Estimates in this publication are based on information collected for a sample of registered motor vehicles, rather than a full enumeration, and are therefore subject to sampling error. They may differ from the data that would have been produced if the information had been obtained for all registered motor vehicles. Examples of the sampling error for this publication are included below.

The sampling error associated with any estimate can be calculated from the sample results. One measure of sampling error is given by the standard error, which indicates the extent to which an estimate might have varied by chance because only a sample of vehicles was included. There are about two chances in three that a sample estimate will differ by less than one standard error from the data that would have been obtained if all vehicles had been included, and about 19 chances in 20 that the difference will be less than two standard errors.

Another measure of sampling variability is the relative standard error (RSE) which is obtained by expressing the standard error as a percentage of the estimate to which it refers. The RSE is a useful measure in that it provides an immediate indication of the percentage error likely to have occurred due to sampling. In this publication, estimates that have an estimated relative standard error between 10% and 25% are annotated with the symbol '^' . These estimates should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% are annotated with the symbol '*', indicating that the estimate should be used with caution as it is subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with the symbol '**' indicating that the sampling variability causes the estimates to be considered too unreliable for general use.

The RSEs relating to 1998, 1999 and 2002 estimates contained in Table 4 of this publication are shown in the following tables.

RSE OF MOTOR VEHICLE USE 1998 (a), State/territory of registration, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL KILOMETRES TRAVELLED (%)
New South Wales
6
16
5
4
5
20
6
4
Victoria
5
33
7
6
7
18
7
4
Queensland
6
30
5
6
7
19
8
4
South Australia
8
21
9
7
7
24
8
6
Western Australia
7
16
10
8
7
20
9
5
Tasmania
7
19
7
8
7
23
9
5
Northern Territory
9
24
10
13
11
31
12
6
Australian Capital Territory
6
22
10
7
11
37
7
5
Australia
3
12
3
3
3
9
3
2

NUMBER OF VEHICLES (%)
New South Wales
3
5
3
1
3
11
9
2
Victoria
3
7
4
3
3
8
5
2
Queensland
3
4
2
4
3
11
4
2
South Australia
3
5
4
4
3
15
4
2
Western Australia
3
4
4
5
4
9
6
2
Tasmania
2
4
3
4
4
11
4
2
Northern Territory
4
6
6
8
6
13
6
3
Australian Capital Territory
3
22
6
8
10
19
7
2
Australia
1
3
1
1
1
4
3
1

AVERAGE KILOMETRES TRAVELLED (%)
New South Wales
5
16
5
4
5
16
7
4
Victoria
5
32
6
6
5
17
6
4
Queensland
6
30
5
6
5
17
7
4
South Australia
7
21
8
7
6
22
8
6
Western Australia
7
16
8
7
7
18
7
5
Tasmania
7
18
7
7
7
23
8
5
Northern Territory
9
23
9
8
10
31
11
6
Australian Capital Territory
6
30
6
9
9
28
6
5
Australia
2
12
2
2
2
8
3
2

(a) These RSEs relate to the estimates in table 4 as published in 9208.0.

RSE OF MOTOR VEHICLE USE 1999 (a), State/territory of registration, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL KILOMETRES TRAVELLED (%)
New South Wales
6
22
8
5
5
15
6
5
Victoria
5
21
10
5
5
18
7
5
Queensland
6
20
7
6
7
48
9
5
South Australia
8
19
9
10
7
37
11
6
Western Australia
7
17
7
6
8
58
13
5
Tasmania
8
20
9
7
9
30
8
6
Northern Territory
10
23
7
7
10
29
14
6
Australian Capital Territory
6
17
8
7
17
37
8
5
Australia
3
10
4
3
3
18
4
2

NUMBER OF VEHICLES (%)
New South Wales
3
5
5
2
3
10
12
2
Victoria
3
4
3
2
3
8
4
2
Queensland
3
7
4
4
4
29
3
2
South Australia
3
6
4
4
3
10
5
2
Western Australia
2
4
5
2
5
21
7
2
Tasmania
4
5
4
3
4
9
4
3
Northern Territory
5
7
5
7
4
18
6
3
Australian Capital Territory
3
5
4
2
10
19
8
2
Australia
1
2
2
1
1
7
4
1

AVERAGE KILOMETRES TRAVELLED (%)
New South Wales
5
22
7
5
5
12
12
4
Victoria
5
21
9
5
4
17
7
4
Queensland
6
19
6
5
6
20
8
4
South Australia
7
19
8
11
7
36
10
6
Western Australia
7
17
7
6
8
40
12
5
Tasmania
8
19
8
6
8
29
8
6
Northern Territory
9
23
7
6
9
30
13
6
Australian Capital Territory
6
17
7
7
10
38
9
5
Australia
3
9
3
3
2
13
4
2

(a) These RSEs relate to the estimates in table 4 as published in 9208.0.

RSE OF MOTOR VEHICLE USE 2002 (a), State/territory of registration, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL KILOMETRES TRAVELLED (%)
New South Wales
5
17
5
4
4
25
7
4
Victoria
5
17
6
5
4
22
9
4
Queensland
6
20
6
6
4
17
7
4
South Australia
6
22
6
6
4
18
8
5
Western Australia
7
22
6
6
6
15
12
5
Tasmania
6
16
8
7
5
23
10
4
Northern Territory
7
27
8
7
11
24
12
5
Australian Capital Territory
5
19
5
7
9
30
7
5
Australia
2
9
3
2
2
10
4
2

NUMBER OF VEHICLES (%)
New South Wales
1
4
4
3
2
13
4
1
Victoria
2
3
3
2
2
9
6
2
Queensland
2
3
4
2
2
8
3
1
South Australia
2
5
2
2
2
7
4
2
Western Australia
2
3
4
2
3
6
7
2
Tasmania
2
4
4
3
4
7
5
1
Northern Territory
2
6
4
2
3
13
10
2
Australian Capital Territory
2
6
5
4
5
20
8
2
Australia
1
2
2
1
1
4
2
1

AVERAGE KILOMETRES TRAVELLED (%)
New South Wales
5
17
5
5
4
19
7
4
Victoria
5
17
6
5
4
20
8
4
Queensland
5
20
5
6
4
14
6
4
South Australia
5
22
6
6
4
16
8
4
Western Australia
7
22
6
6
6
13
10
5
Tasmania
5
15
8
7
6
22
9
4
Northern Territory
6
26
8
7
11
22
12
4
Australian Capital Territory
5
18
6
6
8
23
7
4
Australia
2
9
2
2
2
8
3
2

(a) These RSEs relate to the estimates in table 4 as published in 9208.0.

As an example of the use of an RSE, the 2002 estimate for kilometres travelled by all passenger vehicles registered in Australia is 144,676 million kilometres (Table 4 of the publication). The RSE for this estimate is 2%, as shown above. Therefore, the standard error for the 2002 kilometres travelled by passenger vehicles estimate is 2,894 million kilometres. There are about two chances in three that the figure obtained if all vehicles had been included, would have been in the range 141,782 million kilometres to 147,570 million kilometres. There are about 19 chances in 20 that the figure would have been in the range 138,888 million kilometres to 150,464 million kilometres.

It is important to note that estimates at more detailed levels than the above are subject to higher RSEs and therefore are less reliable.

RSEs for other key variables are shown in the following tables. The RSEs of further detailed variables can be made available on request.

RSE OF FUEL CONSUMPTION 1998 (a), Type of fuel, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL FUEL CONSUMPTION (%)
Petrol
Leaded
7
17
6
16
47
19
21
5
Unleaded
4
16
5
57
95
26
17
3
Total
3
12
4
16
88
18
14
3
Diesel
20
-
7
3
3
12
3
2
LPG/CNG/dual fuel
12
-
12
26
99
27
20
10
Total
3
12
3
3
3
9
3
2

AVERAGE RATE OF FUEL CONSUMPTION (%)
Petrol
Leaded
2
10
2
8
12
14
12
2
Unleaded
3
15
4
60
3
13
11
3
Total
2
11
3
15
4
10
9
2
Diesel
14
-
5
2
2
9
3
3
LPG/CNG/dual fuel
8
-
9
15
1
17
13
6
Total
2
11
2
2
2
6
2
2

- nil or rounded to zero (including null cells).
(a) These RSEs relate to the estimates in table 5 as published in 9208.0.

RSE OF FUEL CONSUMPTION 1999 (a), Type of fuel, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL FUEL CONSUMPTION (%)
Petrol
Leaded
7
16
8
10
49
31
24
6
Unleaded
4
20
6
22
-
34
14
3
Total
3
14
4
9
49
29
13
3
Diesel
21
-
9
3
3
15
4
3
LPG/CNG/dual fuel
15
-
16
20
67
31
21
11
Total
3
14
4
3
3
13
3
2

AVERAGE RATE OF FUEL CONSUMPTION (%)
Petrol
Leaded
2
4
2
8
7
6
14
2
Unleaded
3
17
4
10
-
14
9
3
Total
2
12
3
6
7
13
8
2
Diesel
13
-
7
3
2
9
3
3
LPG/CNG/dual fuel
9
-
13
8
12
17
20
7
Total
2
12
3
2
2
8
3
2

- nil or rounded to zero (including null cells).
(a) These RSEs relate to the estimates in table 5 as published in 9208.0.

RSE OF FUEL CONSUMPTION 2002 (a), Type of fuel, Type of vehicle
Passenger
vehicles
Motor
cycles
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Non-
freight
carrying
trucks
Buses
Total

TOTAL FUEL CONSUMPTION (%)
Petrol
Leaded
20
32
27
53
-
43
53
17
Lead replacement
12
31
18
29
-
28
52
10
Unleaded
3
11
4
50
99
33
16
3
Total
3
9
4
25
99
23
15
2
Diesel
21
100
7
3
2
10
4
3
LPG/CNG/dual fuel
17
97
13
36
54
29
23
13
Total
3
9
3
3
2
9
4
2

AVERAGE RATE OF FUEL CONSUMPTION (%)
Petrol
Leaded
3
10
10
30
-
29
32
3
Lead replacement
3
11
3
18
-
14
52
3
Unleaded
1
2
1
25
97
15
6
1
Total
1
2
1
13
97
15
6
1
Diesel
4
87
2
1
1
5
2
3
LPG/CNG/dual fuel
5
86
5
25
22
17
31
4
Total
1
2
1
1
1
5
2
1

- nil or rounded to zero (including null cells).
(a) These RSEs relate to the estimates in table 5 as published in 9208.0.

RSE OF FREIGHT VEHICLES (a), State/territory of operation
Light
commercial
vehicles
Rigid
trucks
Articulated
trucks
Total

TOTAL TONNE-KILOMETRES (%)
1998
New South Wales
11
9
5
4
Victoria
14
20
7
7
Queensland
11
8
7
5
South Australia
23
18
9
8
Western Australia
16
12
9
8
Tasmania
19
12
9
7
Northern Territory
19
18
12
11
Australian Capital Territory
23
11
33
16
Australia
6
7
4
3
1999
New South Wales
17
14
5
5
Victoria
13
21
5
6
Queensland
12
10
7
6
South Australia
17
13
8
7
Western Australia
18
12
11
9
Tasmania
16
15
11
8
Northern Territory
22
16
16
15
Australian Capital Territory
18
13
24
13
Australia
7
8
4
3
2002
New South Wales
12
9
4
3
Victoria
11
10
4
4
Queensland
15
11
5
4
South Australia
13
15
6
5
Western Australia
16
13
9
7
Tasmania
16
14
7
6
Northern Territory
18
12
15
14
Australian Capital Territory
31
13
29
13
Australia
6
5
3
2

(a) These RSEs relate to the estimates in table 13 as published in 9208.0.

Summary tables in this publication contain estimates from the 1998 to 2002 SMVUs. The SMVU is not designed to minimise the standard errors of the movements between reference periods. Care should be taken in drawing inferences from changes in data over these years. The RSE for the movement can be calculated using:

Formula - RSE
where

Y1t is an estimate of total of the variable of interest, obtained from the 1st time point

Y2t is an estimate of total of the same variable of interest, obtained from the 2nd time point.

Mt is an estimate of movement of the total of the variable of interest from the 1st time
point to the 2nd time point ie Mt = Y2t - Y1t

For total kilometres travelled by type of vehicle from the 1998 and 2002 SMVUs, the RSEs of the movements and the estimates from which they are derived are shown in the following table.

RSE OF THE MOVEMENT OF TOTAL KILOMETRES TRAVELLED
LEVEL ESTIMATES
MOVEMENT ESTIMATES
RSE
RSE
RSE
1998
(1998)
2002
(2002)
Movement
(Movement) (a)
million
%
million
%
million
%

Passenger vehicles
127,586
3
144,676
2
17,090
29
Motor cycles
1,396
12
1,681
9
285
80
Light commercial vehicles
25,851
3
31,349
3
5,498
21
Rigid trucks
6,131
3
7,080
2
948
24
Articulated trucks
4,979
3
5,425
2
445
40
Non-freight trucks
188
9
224
10
36
76
Buses
1,760
3
1,775
4
15
564
Total
167,892
2
192,209
2
24,318
21

(a) Calculated on unrounded data.


From the previous table it can be seen that some of the movements have an RSE of greater than 25%. This indicates that the change in the estimate from one period to the next is subject to sampling variability too high or too unreliable for practical use. It cannot be said with 95% (19 chances in 20) confidence that the movements are significantly different from zero.

NON-SAMPLING ERROR

Non-sampling error covers the range of errors that are not caused by sampling and can occur in any statistical collection whether it is based on full enumeration or a sample. For example, non-sampling error can occur because of non-response to the statistical collection, errors in reporting by providers, definition or classification difficulties, errors in transcribing and processing data and under-coverage of the frame from which the sample was selected. If these errors are systematic (not random) then the survey results will be distorted in one direction and therefore will be unrepresentative of the target population. Systematic errors are called bias.

Two steps undertaken to help minimise non-sampling error are pre-advice and the reduction in the reporting of rounded data. The pre-advice methodology involves vehicle owners receiving early advice about their inclusion in the survey. This encourages a higher degree of record keeping. In addition, the reporting of odometer readings taken at the start and end of the survey periods (approximately three months apart) provide reliable estimates of total distance travelled without a recall bias.

The second step is the reduction in the reporting of rounded data for total distance travelled. Such rounding could cause significant errors, especially with the prevalence of certain distances which could be seen as arbitrary guesses on the part of the provider. Where rounding is identified, providers are contacted and the estimate of their total distance travelled is queried. Distances considered to be rounded are every 1,000 km in the range 1,000 km up to 10,000 km and every 5,000 km for distances over 10,000 km.

Response and non-response

An important factor that affects non-sampling error is the response rate achieved. Responses were received from 81% of all of the selections for 2002. After removing those vehicles that had been found to be deregistered or out of scope, the remaining live response rate for the 2002 SMVU was 80%.

The ABS makes all reasonable efforts to maximise response rates. Where appropriate, mail reminders and telephone follow-up are used to attempt to contact non-responding vehicle owners.

A large non-response increases the potential for non-response bias, which occurs if the usage patterns of the non-responding vehicles differ significantly from those of the responding vehicles. For the SMVU, it is assumed that the characteristics of non-responding vehicles including the proportion of deregistered, out of scope and nil use vehicles are the same as for responding vehicles.

RESPONSE AND NON-RESPONSE, By category
Percentage of selections
Percentage of selections
Percentage of selections
1998
1999
2002

Response received
Registered vehicle
71
73
76
Unregistered vehicle(a)
6
6
5
Non-response
Untraceable - mailing address unknown
11
10
7
Other(b)
12
11
12
Total selections
100
100
100

(a) Includes deregistration, out of scope and duplicates.
(b) Includes responses that were unusable because of unresolved queries or where the vehicle was sold during the reference quarter and the reported data covered less than 14 days; and non-response where no listing could be found to enable contact by telephone, owner contacted by telephone but response still not secured and refusals.

Imputation

The need for imputation of unfilled items on the returned questionnaires, as for previous surveys, remained quite high. Imputation is the process whereby a value is generated for missing data items by averaging the responses for similar vehicles which were operating for the reference period. Of the questionnaires returned for 1998, 1999 and 2002 there were 12%, 14% and 16% respectively of those reporting some vehicle use that needed imputation of one or more items apart from the average rate of fuel consumption. The imputations for average rate of fuel consumption for 1998, 1999 and 2002 were 24%, 26% and 26% respectively.

Adjustments

The SMVU measures the use of all vehicles registered during the reference year. Because selections are taken from vehicles registered some time before the beginning of each collection period, adjustments and additional selections from new motor vehicle registrations are made to account for the change in size of the registered motor vehicle fleet since the population frame was created. This involved two categories:
  • re-registrations - older vehicles that are returning to the registered vehicle fleet after a period of deregistration, and
  • new motor vehicles - vehicles which have not been previously registered.

These activities occur continuously and the adjustments are made to account for the registrations that are estimated to have been added to the registered vehicle fleet between the population frame date and the reference period.

Refer to Technical Note 2: Methodological Review for details of changes made as a result of the review.

Users should contact the ABS if they have any queries on the quality and reliability of estimates for particular purposes.



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