EXPLANATORY NOTES


INTRODUCTION

1 The Household Use of Information Technology (HUIT) statistics presented in this release were compiled from data collected in the 2014-15 Multipurpose Household Survey (MPHS). The MPHS is designed to provide annual statistics for a number of small, self-contained topics and is conducted each financial year throughout Australia from July to June as a supplement to the monthly Labour Force Survey (LFS). The HUIT topic is included in MPHS every two years.

2 The HUIT topic presents details about household and personal internet use providing statistics on:

• households with internet access at home
• reasons for not having internet access at home
• type and number of devices used to access the internet at home
• personal use of the internet
• hours spent online in a typical week
• reasons for personally accessing the internet
• type and number of transactions, of goods or services purchased or ordered online
• whether employed persons accessed the internet for home based work.

3 General demographic information such as age, sex, labour force characteristics, education, and income are also available.


SCOPE

4 The scope of the HUIT topic is restricted to persons aged 15 years and over and excludes the following:

• members of the permanent defence forces
• certain diplomatic personnel of overseas governments usually excluded from census and estimated resident populations
• overseas residents in Australia
• members of non-Australian defence forces (and their dependants)
• people living in Indigenous communities in very remote parts of Australia
• people living in non-private dwellings such as hotels, university residences, students at boarding schools, patients in hospitals, inmates of prisons and residents of other institutions (e.g. retirement homes, homes for persons with disabilities), and
• visitors to private dwellings.

COVERAGE

5 For the HUIT topic, LFS coverage rules are applied which aim to ensure each person is associated with only one dwelling, and hence has only one chance of selection in the survey. See the Explanatory Notes of Labour Force, Australia (cat. no. 6202.0) for more details.


DATA COLLECTION

6 Each month one eighth of the dwellings in the LFS sample were rotated out of the survey and 50% of these dwellings were selected to complete the HUIT topic. In these dwellings, after the LFS had been fully completed for each person in scope and coverage, a person aged 15 years or over was selected at random (based on a computer algorithm) and asked the HUIT questions in a personal interview. If the randomly selected person was aged 15 to 17 years, permission was sought from a parent or guardian before conducting the interview. If permission was not given, the parent or guardian was asked the questions on behalf of the 15 to 17 year old. Data were collected using Computer Assisted Interviewing (CAI), whereby responses were recorded directly onto an electronic questionnaire in a notebook computer, usually during a telephone interview.

7 The publication Labour Force, Australia (cat. no. 6202.0) contains information about survey design, sample redesign, scope, coverage and population benchmarks relevant to the monthly LFS, which also applies to supplementary surveys. It also contains definitions of demographic and labour force characteristics, and information about telephone interviewing relevant to both the monthly LFS and supplementary surveys.


SAMPLE SIZE

8 The initial sample for the 2014-15 HUIT topic was 22,404 private dwellings (from which one randomly selected person per household was asked about their household's access to, and their own use of, the internet). Of the 18,812 private dwellings that remained in the survey after sample loss (e.g. vacant or derelict dwellings, dwellings under construction and dwellings selected in the survey that had no residents in scope for the LFS), 13,686 private dwellings (73%) fully responded to the questions on the household use of information technology.


WEIGHTING, BENCHMARKING AND ESTIMATION

Weighting

9 Weighting is the process of adjusting results from a sample survey to infer results for the total in-scope population. To do this, a 'weight' is allocated to each covered sample unit which can be either a person or a household. The weight is a value which indicates how many population units are represented by the sample unit.

10 The first step in calculating weights for each unit is to assign an initial weight, which is 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 (i.e. they represent 600 people).

Benchmarking

11 The initial weights were then calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks', in designated categories of sex by age by area of usual residence. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons/households which may occur due to either the random nature of sampling or non-response.

12 Person estimates were benchmarked to the projected population in each state and territory, at March 2015. Household estimates were benchmarked to independently calculated estimates of the total number of households in Australia. These estimates do not (and are not intended to) match estimates for the total Australian population or households obtained from other sources.

Estimation

13 Survey estimates of counts of persons or households are obtained by summing the weights of persons or households with the characteristic of interest.

14 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.


RELIABILITY OF ESTIMATES

15 All sample surveys are subject to error which can be broadly categorised as either sampling error or non-sampling error.

Sampling error

16 Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if the total population (as defined for the scope of the survey) had been included in the survey. For more information refer to the Technical Note associated with this release.

Non-sampling error

17 Non-sampling error may occur in any collection, whether it is based on a sample or a full count such as a census. Sources of non-sampling error include non-response, errors in reporting by respondents or recording of answers by interviewers and errors in coding and processing data. Every effort is made to reduce non-sampling error by careful design and testing of questionnaires, training and supervision of interviewers, and extensive editing and quality control procedures at all stages of data processing.


DATA COMPARABILITY

18 Household data in the 2014-15 HUIT are comparable with previous surveys (where those household data items have been collected before).

19 Persons data are not comparable between 2014-15 HUIT and previous surveys. In 2014-15 an internet user is a person aged 15 years or over who accessed the internet for personal use in a typical week, whereas previously an internet user was a person aged 15 years or over who accessed the internet in the last 12 months. The reference period for reasons for accessing the internet also changed from in the last 12 months previously, to in the last 3 months in 2014-15, in line with current Organisation for Economic Co-operation and Development (OECD) standards (see paragraph 21 below). In addition there have been changes to the wording and response categories for some questions in 2014-15 HUIT compared with previous surveys. This includes the identification of those who purchased goods or services over the internet and type of goods or services purchased or ordered online.

Comparability of geographic areas

20 HUIT Survey data for 'Capital City' and 'Balance of State' areas in the 2007-08, 2008-09, 2010-11 and 2012-13 publications were based on Area of Usual Residence boundaries contained in the Australian Statistical Geography Classification (ASGC). The Australian Standard Geographical Classification (ASGS), introduced in 2011, contained new boundaries for Greater Capital City Statistical Areas (GCCSA) and these have been used for the first time in HUIT for 2014-15. The new definitions of Greater Capital City and Rest of State are not comparable with the ASGC boundaries. A suite of geographical correspondences are available to assist users make comparisons and maintain time series between the ASGC and the ASGS, see Australian Statistical Geography Standard (ASGS): Correspondences, July 2011 (cat. no. 1270.0.55.006).

Comparability of international frameworks

21 There are established international frameworks and reporting models for the collection of HUIT statistics (e.g. the OECD model questionnaire of ICT access and use by households and individuals). Suggested question wording from these frameworks have been used as a starting point for HUIT questionnaire design and, where applicable, used in the HUIT survey.

Comparability of state and territory data

22 Due to the age structure of the populations of Australia's states and territories caution should be used when making comparisons. For example, the level of internet use may be a reflection of a younger age profile, rather than general levels of access to the internet.

Comparability with monthly LFS Statistics

23 Due to differences in the scope and sample size of the MPHS (HUIT topic) and that of the LFS, the estimation procedure may lead to some small variations between labour force estimates from this survey and those from the LFS.


FUTURE SURVEYS

24 The ABS will conduct the HUIT topic as part of the MPHS again during the 2016-17 financial year, with the results expected to be available early 2018.


ACKNOWLEDGEMENT

25 ABS surveys 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.


RELATED INFORMATION

26 The Related Information tab associated with this release contains links to a selected range of other ABS publications which may be of interest.

27 Current publications and other products released by the ABS are available from the ABS website. The ABS also issues a daily upcoming release advice on the website that details products to be released in the week ahead.