TECHNICAL NOTE DATA QUALITY
INTRODUCTION
1 Estimates in this publication are based on information obtained from occupants of a sample of dwellings, and are subject to sampling variability. That is, they may differ from those estimates that would have been produced if all dwellings 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 by chance because only a sample of dwellings was included. There are about two chances in three (67%) that a sample estimate will differ by less than one SE from the number 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. Another measure of the likely difference is the relative standard error (RSE), which is obtained by expressing the SE as a percentage of the estimate.
2 Due to space limitations, it is impractical to print the SE of each estimate in the publication. Instead, a table of SEs is provided to determine the SE for an estimate from the size of that estimate ( see table T1). The SE table is derived from a mathematical model, referred to as the 'SE model', which is created using data from a number of past Labour Force Surveys. It should be noted that the SE model only gives an approximate value for the SE for any particular estimate, since there is some minor variation between SEs for different estimates of the same size.
CALCULATION OF STANDARD ERROR
3 An example of the calculation and the use of SEs in relation to estimates of persons is as follows. Table 4 shows the estimated number of female underemployed parttime workers was 446,000. Since this estimate is between 300,000 and 500,000, table T1 shows that the SE for Australia will lie between 6,650 and 8,350 and can be approximated by interpolation using the following general formula:
4 Therefore, there are about two chances in three that the value that would have been produced if all dwellings had been included in the survey will fall within the range 438,100 to 453,900 and about 19 chances in 20 that the value will fall within the range 430,200 to 461,800. This example is illustrated in the following diagram.
5 In general, the size of the SE increases as the size of the estimate increases. Conversely, the RSE decreases as the size of the estimate increases. Very small estimates are thus subject to such high RSEs that their value for most practical purposes is unreliable. In the tables in this publication, only estimates with RSEs of 25% or less are considered reliable for most purposes. Estimates with RSEs greater than 25% but less than or equal to 50% are preceded by an asterisk (e.g.*3.2) to indicate they are subject to high SEs and should be used with caution. Estimates with RSEs of greater than 50%, preceded by a double asterisk (e.g.**0.3), are considered too unreliable for general use and should only be used to aggregate with other estimates to provide derived estimates with RSEs of less than 25%.
MEANS AND MEDIANS
6 The RSEs of estimates of mean duration of insufficient work, median duration of insufficient work and mean preferred number of extra hours are obtained by first finding the RSE of the estimate of the total number of persons contributing to the mean or median ( see table T1) and then multiplying the resulting number by the following factors:
 mean duration of insufficient work: 1.6
 median duration of insufficient work: 2.5
 mean preferred number of extra hours: 0.7
7 The following is an example of the calculation of SEs where the use of a factor is required. Table 4 shows that the estimated number of male underemployed parttime workers was 276,600 with a median duration of insufficient work of 28 weeks. The SE of 276,600 can be calculated from table T1 (by interpolation) as 6,400. To convert this to an RSE we express the SE as a percentage of the estimate or 6,400/276,600 = 2.3%.
8 The RSE of the estimate of median duration of insufficient work is calculated by multiplying this number (2.3%) by the appropriate factor shown in paragraph 6 (in this case 2.5): 2.5 x 2.3 = 5.8%. The SE of this estimate of median duration of insufficient work is therefore 5.8% of 28, i.e. about 2 (rounded to the nearest whole week). Therefore, there are two chances in three that the median duration of insufficient work for males that would have been obtained if all dwellings had been included in the survey would have been within the range 2630 weeks, and about 19 chances in 20 that it would have been within the range 2432 weeks.
PROPORTIONS AND PERCENTAGES
9 Proportions and percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. A formula to approximate the RSE of a proportion is given below. This formula is only valid when x is a subset of y.
10 Considering the example from paragraph 3, of the 446,000 female underemployed parttime workers, 178,800 or 40.1% had insufficient work for 52 weeks and over. The SE of 178,800 may be calculated by interpolation as 5,300. To convert this to an RSE we express the SE as a percentage of the estimate, or 5,300/178,800 = 3.0%. The SE for 446,000 was calculated previously as 7,900, which converted to an RSE is 7,900/446,000 = 1.8%. Applying the above formula, the RSE of the proportion is:
11 Therefore, the SE for the proportion of females who have a current period of insufficient work of 52 weeks or more is 1.0 percentage points (=(40.1/100)x2.4). Therefore, there are about two chances in three that the proportion of females who have a current period of insufficient work of 52 weeks or more was between 39.1% and 41.1% and 19 chances in 20 that the proportion is within the range 38.1% to 42.1%.
DIFFERENCES
12 Published estimates may also be used to calculate the difference between two survey estimates (of numbers or percentages). Such an estimate is subject to sampling error. The sampling error of the difference between two estimates depends on their SEs and the relationship (correlation) between them. An approximate SE of the difference between two estimates (xy) may be calculated by the following formula:
13 While this formula will only be exact for differences between separate and uncorrelated characteristics or subpopulations, it is expected to provide a good approximation for all differences likely to be of interest in this publication.
STANDARD ERRORS
T1 STANDARD ERRORS OF ESTIMATES 

         AUST. 
 NSW  Vic.  Qld  SA  WA  Tas.  NT  ACT  SE  RSE 
Size of Estimate (persons)  no.  no.  no.  no.  no.  no.  no.  no.  no.  % 

100  290  290  220  180  220  110  80  100  110  110.0 
200  400  380  320  240  290  160  120  170  190  95.0 
300  470  440  390  280  340  190  160  210  260  86.7 
500  580  540  500  340  420  240  200  270  380  76.0 
700  660  620  580  390  480  270  230  300  480  68.6 
1000  760  710  680  450  550  310  270  330  610  61.0 
1500  900  830  810  530  640  360  320  360  780  52.0 
2000  1 010  930  910  590  710  390  350  390  920  46.0 
2500  1 100  1 000  1 000  650  800  400  400  400  1 050  42.0 
3000  1 200  1 100  1 050  700  850  450  400  450  1 150  38.3 
3500  1 250  1 150  1 100  700  900  450  400  450  1 250  35.7 
4000  1 300  1 200  1 200  750  900  500  450  450  1 350  33.8 
5000  1 450  1 300  1 250  800  1 000  500  500  500  1 500  30.0 
7000  1 650  1 500  1 450  900  1 150  600  600  600  1 700  24.3 
10000  1 850  1 700  1 600  1 050  1 300  700  750  700  2 000  20.0 
15000  2 150  1 950  1 800  1 200  1 500  850  1 050  850  2 350  15.7 
20000  2 400  2 200  1 950  1 350  1 650  1 000  1 300  1 000  2 550  12.8 
30000  2 800  2 550  2 250  1 550  1 900  1 250  1 850  1 250  2 900  9.7 
40000  3 100  2 800  2 500  1 800  2 100  1 500  2 300  1 500  3 150  7.9 
50000  3 350  3 050  2 750  2 000  2 300  1 700  2 750  1 650  3 400  6.8 
100000  4 250  4 000  3 750  3 000  3 400  2 400  4 800  2 250  4 300  4.3 
150000  5 000  4 850  4 600  3 850  4 450  2 850  6 600  2 500  5 000  3.3 
200000  5 750  5 650  5 400  4 550  5 350  3 200  8 250  2 650  5 600  2.8 
300000  7 250  7 250  6 850  5 550  6 750  3 700  11 250  2 800  6 650  2.2 
500000  10 150  10 050  9 250  7 000  8 600  4 250  . .  2 800  8 350  1.7 
1000000  15 100  15 250  13 200  8 900  10 950  4 850  . .  . .  11 750  1.2 
2000000  20 350  22 550  17 700  10 600  12 700  . .  . .  . .  17 050  0.9 
5000000  25 900  36 100  23 900  11 900  13 250  . .  . .  . .  28 450  0.6 
10000000  27 750  49 750  27 950  . .  . .  . .  . .  . .  37 950  0.4 
15000000  . .  . .  . .  . .  . .  . .  . .  . .  42 850  0.3 

. . not applicable 
T2 LEVELS AT WHICH ESTIMATES HAVE RELATIVE STANDARD ERRORS OF 25% AND 50%(a) 

 NSW  Vic.  Qld  SA  WA  Tas.  NT  ACT  Aust. 
Percentage  no.  no.  no.  no.  no.  no.  no.  no.  no. 

RSE of 25%  6 300  5 400  5 100  2 600  3 500  1 400  1 200  1 400  6 800 
RSE of 50%  2 000  1 800  1 700  800  1 200  500  300  600  1 600 

(a) Refers to the number of persons contributing to the estimate. 