Scotland's People Annual Report: Results from 2012 Scottish Household Survey

Annex 1 Using the information in this report

How data is displayed in tables

All tables are presented in the format 'dependent variable by independent variable' where the independent variable is being used to examine or explain variation in the dependent variable. Thus, a table titled 'housing tenure by household type' shows how housing tenures vary among different household types. Where the tables show column percentages, the dependent variable is shown in the rows and the columns show the independent variable. Where the tables show row percentages, this is switched and the dependent variable is shown in the columns. Some summary tables combine three dimensions, for example agreement by age within statement. These are shown as cell percentages.

All tables have a descriptive and numerical base showing the population or population sub-group examined in it. While all results have been calculated using weighted data, the bases shown provide the unweighted counts, which have been rounded to the nearest 10 to comply with disclosure control principles of the Code of Practice for Official Statistics. It should therefore be noted that the results and bases presented cannot be used to calculate how many respondents gave a certain answer.

Reporting conventions

In general, percentages in tables have been rounded to the nearest whole number. Zero values are shown as a dash (-), values greater than 0% but less than 0.5% are shown as 0% and values of 0.5% but less than 1% are rounded up to 1%. Columns or rows may not add to 100% because of rounding, where 'don't know/refused' answers are not shown^[91] or where multiple responses to a question are possible.

In some tables, percentages have been removed from columns and replaced with '*' where the base on which percentages would be calculated is less than 50. This data is judged to be insufficiently reliable for publication.

Variations in base size for totals

As the questionnaire is administered using computer assisted personal interviewing (CAPI), item non-response is kept to a minimum. Bases do fluctuate slightly due to small amounts of missing information (where, for example, the age or sex of household members has been refused and where derived variables such as household type use this information).

Some questions are asked of a reduced sample and the bases are correspondingly lower. From January 2012, the redesigned survey asked questions either of full or one-third sample allocation. This concept of streaming was first introduced to the SHS in 2007, when some questions were streamed or changed in the course of the year and again the base size is lower. Further changes to streaming was made in both 2008 and 2009 alongside any other changes to questions across the different years.

The sample base annex (Annex 3) gives details of frequencies and bases for the main dependent variables.

Statistical significance

All proportions produced in a survey have a degree of error associated with them because they are generated from a sample of the population rather than the population as a whole. Any proportion measured in the survey has an associated confidence interval (within which the 'true' proportion of the whole population is likely to lie), usually expressed as ±x%. It is possible with any survey that the sample achieved produces estimates that are outside this range. The number of times out of a 100 surveys when the result achieved would lie within the confidence interval is also quoted; conventionally the level set is 95 out of 100, or 95%.^[92] Technically, all results should be quoted in this way. However, it is less cumbersome to simply report the percentage as a single percentage, the convention adopted in this report.

Where sample sizes are small or comparisons are made between sub-groups of the sample, the sampling error needs to be taken into account. There are formulae to calculate whether differences are statistically significant (i.e. they are unlikely to have occurred by chance) and Annex 4 provides a simple way to estimate if differences are significant.