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6278.0 - Education and Training Experience, 2009 Quality Declaration 
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EXPLANATORY NOTES


INTRODUCTION

1 The statistics in this publication were compiled from data collected in the Survey of Education and Training (SET) which was conducted throughout Australia from March to June 2009.

2 The SET provides a range of key indicators on educational participation, attainment and learning. Detailed information on the following topics was collected:

  • General demographic information
  • Parental information
      • educational attainment
      • employment status
      • occupation
  • Employment characteristics
      • labour force status
      • occupation
      • industry
      • sector of employment
      • duration of employment or unemployment
      • hours worked
      • trade union membership
  • Participation in education
      • school
      • current study
      • educational attainment
      • formal learning in the last 12 months
  • Education and employment outcomes
      • first qualification
      • most recent qualification
      • Non-formal learning
      • work-related courses
      • types of financial support
      • types of expenses
      • participation in training
      • time spent on training
      • training costs
      • Informal learning
  • Barriers to learning
      • access
      • difficulties
  • Health and disability
  • Personal income

3 The statistics included in this publication present a broad overview of the data items collected in the SET. Emphasis has been given to providing information on key measures such as educational attainment and participation in education and training.


SCOPE OF THE SURVEY

4 The SET is a household survey which was conducted in both urban and rural areas in all states and territories, except for very remote parts of Australia. Queensland, South Australia, Western Australia and the Northern Territory all have very remote areas. With the exception of the Northern Territory, the population living in very remote areas represents only a small proportion of the total population (approximately 2%). For this, and other practical reasons, no adjustment was made to state population benchmarks when deriving the survey results. This exclusion is unlikely to impact on national estimates, and will only have a minor impact on any aggregate estimates that are produced for individual states and territories, except the Northern Territory where the excluded population accounts for over 23% of persons.

5 Only people who were usual residents of private dwellings in Australia were covered by the SET. Private dwellings are houses, flats, home units and any other structures used as private places of residence at the time of the survey. People usually resident in non-private dwellings such as hotels, motels, hostels, hospitals and short-stay caravan parks were not included in the survey. Usual residents are those persons who usually live in a particular dwelling and regard it as their own or main home. Visitors to private dwellings are not included in the interview for that dwelling. However, if they are a usual resident of another dwelling that is in the scope of the survey they have a chance of being selected in the survey or, if not selected, they will be represented by similar persons who are selected in the survey.

6 Persons aged 15-74 years were included in the scope of the SET. The bulk of the questionnaire was asked of persons in the population of interest which is those aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. Persons aged 65-74 years who were in scope but not in the population of interest were sequenced to the end of the questionnaire once their labour force status had been established.

7 The following non-residents were excluded from the resident population estimates used to benchmark the SET results, and were not interviewed:
  • diplomatic personnel of overseas governments;
  • persons whose usual place of residence was outside Australia;
  • members of non-Australian defence forces (and their dependants) stationed in Australia.


SURVEY DESIGN

Sample size and selection

8 The 2009 SET was designed to provide reliable estimates at the national level and for each state and territory.

9 Dwellings in each state and territory were selected at random using a multi-stage area sample of private dwellings. The initial sample for the 2009 SET consisted of approximately 16,400 private dwellings. Of the approximately 13,200 households that remained in the survey after sample loss, approximately 11,800 (89%) were fully responding. As well as persons from fully responding households, SET included 452 fully responding persons from 292 partially responding households. The inclusion of these persons had an impact on the estimation of household income because of non-response by other members and this is further discussed in paragraph 31. In total, 23,807 persons fully responded to the 2009 SET.

SET FINAL SAMPLE, Number of persons - 2009

Capital City
Balance of State or Territory
Total
'000
'000
'000

New South Wales
2 271
1 460
3 731
Victoria
2 333
1 051
3 384
Queensland
1 372
1 577
2 949
South Australia
2 034
801
2 835
Western Australia
2 245
909
3 154
Tasmania
1 172
1 923
3 095
Northern Territory
1 371
406
1 777
Australian Capital Territory
2 882
-
2 882
Australia
15 680
8 127
23 807

- nil or rounded to zero (including null cells)


Non-responding households

10 Approximately 3,230 households in the 2009 SET did not respond at all to the questionnaire, or did not respond adequately. Such households included:
  • households affected by death or illness of a household member
  • households in which person(s) in the household did not respond because they could not be contacted, had language problems or refused to participate
  • households in which person(s) did not respond to key questions.

Partial response

11 Some households did not supply all the required information but supplied sufficient information to be retained in the SET sample. Such partial response occurred when:
  • at least one in scope person in the household responded but information could not be collected from the entire household. The information from the responding member(s) of the household was included however, some household details such as the estimation of household income are missing as information from all members of the household is incomplete.
  • earnings, income or training cost information is missing from a person's record because they are unable or unwilling to provide the data but they responded to other key variables in the survey.


DATA COLLECTION

12 Trained ABS interviewers conducted personal interviews at selected dwellings from the beginning of March 2009 to the end of June 2009. Interviews were conducted using a Computer Assisted Interviewing (CAI) questionnaire. CAI involves the use of a notebook computer to record, store, manipulate and transmit the data collected during interviews.

13 One person in the household, aged 18 years or over, provided basic household information including age, sex, Indigenous status, country of birth and relationships for all household members. Personal interviews were then conducted with all persons aged 15-74 years. The bulk of the questionnaire was asked of persons in the population of interest which is those aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. Persons aged 65-74 years who were in scope but not in the population of interest were sequenced to the end of the questionnaire once their labour force status had been established.


WEIGHTING, BENCHMARKING AND ESTIMATION

Weighting

14 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 person. The weight is a value which indicates how many population units are represented by the sample unit.

15 The first step in calculating weights for each person is to assign an initial weight, which is equal to the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 people).

Benchmarking

16 The SET weights were calibrated to align with independent estimates of the population by sex, age, state or territory of usual residence, section of state or territory and labour force status. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than to the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons which may occur due to either the random nature of sampling or non-response.

17 The 2009 SET was benchmarked to the estimated resident population (ERP) aged 15-74 years living in private dwellings in each state and territory, excluding the ERP living in very remote areas of Australia, at May 2009. The SET estimates do not (and are not intended to) match estimates for the total Australian resident population obtained from other sources (which include persons and households living in non-private dwellings such as hotels and boarding houses, and in very remote parts of Australia).

Estimation

18 Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristic of interest. Estimates of other counts (i.e. training courses and qualifications) are obtained by multiplying the characteristic of interest by the weight of the reporting person, and then aggregating.


RELIABILITY OF ESTIMATES

19 All sample surveys are subject to error which can be broadly categorised as either:
  • sampling error; or
  • non-sampling error.

20 Sampling error occurs because only a small proportion of the total population is used to produce estimates that represent the whole population. Sampling error can be reliably measured as it is calculated based on the scientific methods used to design surveys.

21 Non-sampling error may occur at any stage throughout the survey process. For example, persons selected for the survey may not respond (non-response); survey questions may not be clearly understood by the respondent; responses may be incorrectly recorded by interviewers; or there may be errors in coding or processing survey data.

Sampling error

22 Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if all persons in scope of the survey had been included. A measure of the sampling error for a given sample estimate is provided by the standard error, which may be expressed as a percentage of the estimate (relative standard error (RSE)). In this publication estimates with an RSE of 25% to 50% are preceded by an asterisk (e.g. *15.7) to indicate that the estimate should be used with caution. Estimates with RSEs over 50% are indicated by a double asterisk (e.g.**2.8) and should be considered unreliable for most purposes. For more information refer to the Technical Notes.

Non-sampling error

23 Non-sampling error may occur in any collection, whether it is based on a sample or a full count such as a census. One of the main sources of non-sampling error is non-response by persons selected in the survey. Non-response can affect the reliability of results and can introduce bias. The magnitude of any bias depends upon the level of non-response and the extent of the difference between the characteristics of those people who responded to the survey and those who did not.

24 Non-response occurs when persons cannot or will not cooperate, or cannot be contacted. Non-response can affect the reliability of results and can introduce a bias. The magnitude of any bias depends upon the rate of non-response and the extent of the difference between non-respondents' characteristics and those of persons who responded to the survey.

25 To reduce the level and impact of non-response the following methods were adopted in this survey:
  • face-to-face interviews with respondents;
  • the use of interviewers who could speak languages other than English where necessary;
  • follow-up of respondents if there was initially no response;
  • ensuring the weighted file is representative of the population by aligning the estimates with population benchmarks.

26 Every effort was made to reduce other non-sampling error by careful design and testing of the questionnaire, training and supervision of interviewers, and extensive editing and quality control procedures at all stages of data processing.

27 An advantage of the CAI technology used to conduct interviews for this survey is that it potentially reduces non-sampling errors by enabling edits to be applied as the data are being collected. The interviewer is alerted immediately if information entered into the computer is either outside the permitted range for that question, or contradictory to information previously recorded during the interview. These edits allow the interviewer to query respondents and resolve issues during the interview. CAI sequencing of questions is also automated so that respondents are only asked relevant questions and in the appropriate sequence, eliminating interviewer sequencing errors.


REFERENCE PERIOD AND SEASONAL EFFECTS

28 The estimates in this publication are based on information collected from March 2009 to June 2009 and, due to reference period and seasonal effects, they may not be fully representative of other time periods in the year. For example, the SET collected information on current study relating to persons enrolled in study at the time of their interview. As the period of collection for SET was from March to June, the reference period for data items on current study was four months. Estimates therefore include enrolments in the first half of 2009, as well as some enrolments which commenced in the second half of 2009. Enrolments are also subject to seasonal variation through the year. Therefore, the SET results could have differed if the survey had been conducted over the whole year or in a different part of the year.


INTERPRETATION OF RESULTS

29 Care has been taken to ensure that the results of this survey are as accurate as possible. All interviews were conducted by trained ABS officers. Extensive reference material was developed for use during field enumeration and intensive training was provided to interviewers. There remain, however, other factors which may have affected the reliability of results, and for which no specific adjustments can be made. The following factors should be considered when interpreting the 2009 SET estimates:
  • Information recorded in this survey is essentially 'as reported' by respondents, and hence may differ from information available from other sources or collected using different methodologies.
  • Responses may be affected by imperfect recall or individual interpretation of survey questions.
  • Some respondents may have provided responses that they felt were expected, rather than those that accurately reflected their own situation.

30 In addition, some respondents were unwilling or unable to provide the required information for a number of SET data items. Where responses for a particular data item were missing for a person or household they were recorded in a 'not known' or 'not stated' category for that data item. These 'not known' or 'not stated' categories are not explicitly shown in the publication tables, but have been included in the totals. Publication tables presenting proportions have included any 'not known' or 'not stated' categories in the calculation of these proportions.

31 For the personal gross weekly income data item, approximately 2000 people (8%) did not provide an income amount, either because they did not know their income or they refused to answer. Household income is the sum of the personal income of each person aged 15 years and over in the household. Where one person in the household either refused or did not know their income, the income for the household had to be classified as 'not known'. In some households, not all persons responded to the survey however, the records for those persons who did respond were included. Household income for these persons also had to be classified as 'not known'. Mean and median income excluded those households whose income was not known or inadequately reported. There were a number of other data items included in the publication that had missing values. The proportions of these missing values did not exceed 16% for any data item.

INCOME NON-REPONSE, Persons age 15-74

no.
%

Personal gross weekly income refused/not known
1 979.0
8.3
Total household gross weekly income not known due to personal income refused/not known
3 243.0
13.6
Total household gross weekly income not known due to partially responding household
452.0
1.9
Equivalised household gross weekly income not known
3 695.0
15.5




CLASSIFICATIONS

32 The 2009 SET used the following Australian standard classifications.

Country of Birth

33 Country of birth data were classified according to the Standard Australian Classification of Countries (SACC), Second Edition, 2008 (cat. no. 1269.0). The Second Edition amended the Standard Australian Classification of Countries (SACC), 1998 (cat. no. 1269.0) and its subsequent revisions, in incorporating country changes and detailing updated correspondence with the International Organization for Standardization (ISO) and United Nations (UN) classification codes, as well as outlining valid output code options for some supplementary codes. These revisions have been effective since 19 May 2008. The 2009 SET questionnaire listed the 10 most frequently reported countries on the basis of the statistical significance of these languages in the Australian context. Interviewers were instructed to mark the appropriate box, or if the reported country was not among those listed, to record the name of the country for subsequent coding.

Education

34 Education data were coded to the Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0). The ASCED is a national standard classification which can be applied to all sectors of the Australian education system including schools, vocational education and training and higher education. The ASCED comprises two classifications: Level of Education and Field of Education.

35 Field of Education is defined as the subject matter of an educational activity. Fields of education are related to each other through the similarity of subject matter, through the broad purpose for which the education is undertaken, and through the theoretical content which underpins the subject matter. There are 12 broad fields, 71 narrow fields and 356 detailed fields. For definitions of these fields see the Australian Standard Classification of Education, 2001 (cat. no. 1272.0).

36 Level of Education is defined as a function of the quality and quantity of learning involved in an educational activity. There are nine broad levels, 15 narrow levels and 64 detailed levels. For definitions of these levels see the Australian Standard Classification of Education, 2001 (cat. no. 1272.0).

37 The relationship between categories in the Level of Education classification should be essentially ordinal. In other words, educational activities at Broad Level 1 Postgraduate Degree should be at a higher level than those at Broad Level 2 Graduate Diploma and Graduate Certificate, and so on. However, when this idea is applied to the reality of educational provision in Australia, it is not always possible to assert that an ordinal relationship exists among the various levels of education.

38 This is particularly evident in the case of the relationship between Certificates I-IV in Broad Level 5 Certificate Level, and School Education included in Broad Level 6 Secondary Education. In this instance, the level of education associated with secondary education may range from satisfying the entry requirements for admission to a university degree course, to the completion of units in basic literacy, numeracy and life skills. Educational activity in these categories may therefore be of an equal, higher or lower level than Certificates found in Broad Level 5 Certificate Level.

39 Level of highest educational attainment was derived from information on highest year of school completed and level of highest non-school qualification. The derivation process determined which of the 'non-school' or 'school' attainments would be regarded as the highest. Usually the higher ranking attainment is self-evident, but in some cases some secondary education is regarded, for the purposes of obtaining a single measure, as higher than some certificate level attainments.

40 The following decision table was used to determine which of the responses to questions on highest year of school completed (coded to ASCED Broad Level 6) and level of highest non-school qualification (coded to ASCED Broad Level 5) was regarded as the highest. It is emphasised that this table was designed for the purpose of obtaining a single value for level of highest educational attainment and is not intended to convey any other ordinality.

Diagram: Decision Table: Level of Highest Educational Attainment

41 The decision table was also used to rank the information provided in the SET about the qualifications and attainments of a single individual. It does not represent any basis for comparison between differing qualifications. For example, a person whose highest year of school completed was Year 12, and whose level of highest non-school qualification was a Certificate III, would have those responses crosschecked on the decision table and would as a result have their level of highest educational attainment output as Certificate III. However, if the same person answered 'certificate' to the highest non-school qualification question, without any further detail, it would be crosschecked against Year 12 on the decision table as Certificate not further defined. The output would then be Year 12. The decision table, therefore, does not necessarily imply that one qualification is 'higher' than the other. For more details, see Education Variables, 2002 (cat. no. 1246.0).

42 Level of education of current study was also derived using the decision table displayed above, taking into account Level of education of school study in current year and Level of education of non-school study in current year for persons who were undertaking concurrent qualifications.

Geography

43 Geographical data were classified according to the Australian Standard Geographical Classification (ASGC) (cat. no. 1216.0).

Industry

44 Industry data were classified according to the Australian and New Zealand Standard Industrial Classification (ANZIC), 2006 (cat. no. 1292.0).

Language

45 All responses to language questions were coded to the Australian Standard Classification of Languages (ASCL), Second Edition, 2005-06 (cat. no. 1267.0). The 2009 SET questionnaire listed the 10 most frequently reported languages first spoken at home and the 10 most frequently reported main languages spoken at home on the basis of the statistical significance of these languages in the Australian context. Interviewers were instructed to mark the appropriate box, or if the reported language was not among those listed, to record the name of the language for subsequent coding.

Occupation

46 Occupation data were classified according to the Australian and New Zealand Standard Classification of Occupations (ANZSCO), First Edition, 2006 (cat. no. 1220.0).


COMPARABILITY OF TIME SERIES

47 Results from the five previous household surveys on this topic were published in Education and Training Experience, Australia, 2005 (cat. no. 6278.0), Education and Training Experience, Australia, 2001 (cat. no. 6278.0), Education and Training Experience, Australia, 1997 (cat. no. 6278.0), Training and Education Experience, Australia, 1993 (cat. no. 6278.0) and How Workers Get their Training 1989 (cat. no.6278.0).

48 Essentially the same methodology has been used since 1993 however the scope of the surveys has differed. While the scope of the 2009 survey included persons aged 15-74, the questions focused on persons aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. The 2005 survey included all persons aged 15 years and over, with those aged 70 years and over asked a subset of questions, regardless of their employment status. The 2001 survey included all persons aged 15-64 years. In comparison, the scope of the 1997 survey was narrower and included persons aged 15-64 years who:
  • had worked as wage or salary earners in the previous 12 months;
  • were employed, unemployed or marginally attached to the labour force;
  • were aged 15-20 years and still at secondary school; and
  • were not in the labour force but were studying, or had studied in 1997.

49 The scope of the 1993 survey was even narrower than that of the 1997 survey. It included persons aged 15-64 years who had worked as wage or salary earners ('employees') in the last 12 months, as well as those who, at the time of the survey, were employers, self-employed, unemployed or marginally attached to the labour force, except:
  • persons aged 15-20 years still at school; and
  • persons working as unpaid family helpers or solely for payment in kind unless they had also held a wage or salary job in the last 12 months.

50 Other main differences between the surveys are as follows:
51 There have also been a number of key questionnaire changes since the 2005 cycle which include:
  • the collection of detailed information about all qualifications completed (maximum 15) compared with only the three highest qualifications in 2005;
  • the introduction of an education and employment outcomes topic based on the 'First completed' and the 'Most recent completed' non-school qualification(s);
  • adopting the concepts of participation in formal, non-formal and informal learning undertaken in the last 12 months based on the international Classification of learning activities (CLA) which was developed by Eurostat and released in July 2006;
  • the collection of data about informal learning;
  • significant definitional changes to the 'work-related training' module which occurred as a result of a major review of SET, involving consultation with key stakeholders, which was undertaken during 2007. As the 'work-related training' data items are not comparable over time they should not be used in conjunction with the data in earlier editions of this publication.
  • the collection of parental information (employment and education) for persons aged 15-24 years;
  • the collection of data about time spent on formal learning and associated costs;
  • changes to the collection of employment and income information to align with new ABS standards.

52 Selected summary results from the 2005 SET have been presented in this publication to allow comparisons over time to be made. The statistical significance of data changes between 2005 and 2009 has been investigated and results that are statistically significant are indicated in tables 4, 10, 12 and 16. A detailed listing outlining the comparability of data items between the 2005 and 2009 cycles will be made available on the ABS website to coincide with the release of the confidentialised unit record files (CURFs) to assist users with understanding the comparability of SET data over time.

53 The National Centre for Education and Training Statistics (NCETS) in the ABS can provide further advice on the comparability of the 2009 survey results with those from earlier surveys.


COMPARABILITY WITH OTHER ABS SOURCES

54 Estimates from the SET may differ from the estimates produced from other ABS collections for several reasons. The SET is a sample survey and its results are subject to sampling error. Results may differ from other sample surveys, which are also subject to sampling error. Users should take account of the RSEs on estimates and those of other survey estimates where comparisons are made.

55 Differences in SET estimates, when compared with the estimates of other surveys, may also result from:
  • differences in scope and/or coverage;
  • different reference periods reflecting seasonal variations;
  • non-seasonal events that may have impacted on one period but not another; or
  • because of underlying trends in the phenomena being measured.

56 Finally, differences can occur as a result of using different collection methodologies. This is often evident in comparisons of similar data items reported from different ABS collections where, after taking account of definition and scope differences and sampling error, residual differences remain. These differences are often the result of the mode of the collections, such as whether data are collected by an interviewer or self-enumerated by the respondent, whether the data are collected from the person themselves or from a proxy respondent, and the level of experience of the interviewers. Differences may also result from the context in which questions are asked, i.e. where in the interview the questions are asked and the nature of preceding questions. The impacts on data of different collection methodologies are difficult to quantify. As a result, every effort is made to minimise such differences.

57 The following table presents comparisons between a number of key SET data items and similar data items from other ABS sources. These sources include data collected in the Survey of Education and Work (SEW), which were reported in the 2009 issue of Education and Work, Australia, May 2009 (cat. no. 6227.0) and data collected from the Adult Literacy and Life Skills Survey (ALLS), which were reported in the Adult Literacy and Life Skills Survey, Summary Results (cat. no.4228.0). The comparison shows SET data are broadly consistent with these ABS sources.

COMPARISON OF DATA FROM SET WITH OTHER ABS SOURCES, Persons aged 15-64 years

SET
SEW
ALLS
%
%
%

Highest year of school completed
Year 12
51.0
54.0
50.0
Year 11
12.0
11.0
12.0
Year 10 or below(a)
36.0
34.0
39.0
Level of highest non-school qualificaiton
Postgraduate Degree/Graduate Diploma/Graduate Certificate
8.0
7.0
6.0
Bachelor degree
14.0
16.0
15.0
Advanced Diploma/Diploma
10.0
9.0
9.0
Certificate III and IV
17.0
16.0
16.0
Certificate I and II
6.0
5.0
7.0
Total(b)
57.0
55.0
56.0
Main field of highest non-school qualificaiton
Natural and Physical Sciences
2.0
2.0
2.0
Information Technology
2.0
2.0
2.0
Engineering and Related Technologies
9.0
10.0
10.0
Architecture and Building
3.0
4.0
3.0
Agriculture Environmental and Related Studies
1.0
1.0
2.0
Health
5.0
5.0
5.0
Education
4.0
4.0
4.0
Management and Commerce
13.0
13.0
14.0
Society and Culture
7.0
8.0
7.0
Creative Arts
3.0
2.0
3.0
Food Hospitality and Personal Services
3.0
3.0
4.0
Labour force status
Full-time
50.0
53.0
53.0
Part-time
22.0
22.0
23.0
Unemployed
5.0
5.0
4.0
Not in the Labour Force
23.0
21.0
20.0
Country of birth
Born in Australia
72.0
71.0
73.0
Born overseas
28.0
29.0
27.0

(a) Includes persons who never attended school.
(b) Includes 'Certificate n.f.d' and 'Level not determined'.


58 Although both the SET and the SEW are education surveys, there are a number of key differences between them. Conducted on an annual basis, the SEW provides a range of key indicators of educational participation and attainment and data on people's transition between education and work, and involvement in apprenticeships and traineeships. Conversely, the SET is conducted every four years and provides data on the level and outcomes of the individuals education and training. The SET's additional content includes aspects such as income, more extensive education history, and health and disability. The scope of the SEW is broadly the same as the SET however SEW is based on household interviews with any responsible adult whereas the SET interviews each person in the household who is in scope.


SET PRODUCTS AND SERVICES

59 Below is information describing the range of data to be made available from the 2009 Survey of Education and Training, both in published form and on request. Products available on the ABS website <www.abs.gov.au> are indicated accordingly.

Education and Training Experience, Australia, 2009 datacubes

60 An electronic version of the tables contained in this publication is available on the ABS website (cat. no. 6278.0), in spreadsheet format. The spreadsheet presents RSEs relating to estimates and/or proportions for each publication table.

State/territory tabulations

61 A set of tables in spreadsheet format equivalent to those in this publication will be produced for each state and territory (subject to standard error constraints and excluding time series tables). These tables will be available from the ABS web site <www.abs.gov.au> as Datacubes (Education and Training Experience, State and Territory tables, Australia cat. no. 6278.0.55.005) in April 2010.

Microdata

62 For users who wish to undertake more detailed analysis, microdata from the 2009 SET will be available in May 2010. The microdata will be released in the form of two confidentialised unit record files (CURFs), the basic CURF (Survey of Education and Training: Basic CURF, Australia cat. no. 6278.0.55.002) and the expanded CURF (Survey of Education and Training: Expanded CURF, Australia cat. no. 6278.0.55.004). The expanded CURF will contain more detail than the basic CURF and will only be available via the Remote Access Data Laboratory (RADL), which is a secure Internet-based data query service. The basic CURF will be available via CD ROM or RADL.

63 Technical information describing the content and use of the basic and expanded SET CURFs will be available in the Technical Manual: Survey of Education and Training, CURF, Australia: Confidentialised Unit Record File (cat. no. 6278.0.55.001). Up-to-date information on the ABS RADL service, including information on pricing, 'Applications & Undertakings', and a training manual outlining obligations and responsibilities when accessing ABS microdata, is available on the ABS website via the following link; Remote Access Data Laboratory (RADL). Those wishing to access the 2009 SET microdata should contact the ABS using MiCRO, the ABS online CURF registration system.

Data available on request

64 Special tabulations of SET data are available on request and for a fee. Subject to confidentiality and sampling variability constraints, tabulations can be produced from the survey incorporating data items, populations and geographic areas selected to meet individual requirements. These can be provided in printed or electronic form. Please contact the National Information and Referral Service on 1300 135 070 or client.services@abs.gov.au for further information about these or related statistics.


ACKNOWLEDGMENT

65 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905 (CSA).


RELATED PUBLICATIONS

66 Listed below is a selection of other ABS publications on related topics which may be of interest. Information about previous and upcoming ABS publications and products can be found on the ABS website <www.abs.gov.au>. The ABS also issues a Release Calendar which shows the expected release dates for the upcoming six months.
67 The Education and Training theme page also contains a wealth of information and useful references.


NEXT SURVEY

68 The ABS intends to conduct the SET again in 2013.


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