Scotland's People
Results from the 2003 Scottish Household Survey Annual Report
2 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.
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 give the unweighted counts. It should therefore be noted that the results and bases presented cannot be used to calculate how many respondents gave a certain answer.
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 that 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 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 100. This data is judged to be insufficiently reliable for publication. |
Variations in base sizes for tables
Because the questionnaire is administered using Computer Assisted Personal Interveiwing (CAPI), item non-response is kept to a minimum. Bases occasionally 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 apply only to individual survey years and the bases are correspondingly lower. Occasionally, questions are introduced in the course of a survey year and again the base size is lower.
The sample base appendix gives details of frequencies and bases for the main dependent variables.
Income imputation
One section of the questionnaire is substantially affected by missing information. In the section on household income, approximately 33% of respondents either refuse to answer the questions or are unable to provide information that is sufficiently reliable to report, for example, because there are no details of the level of income received for one or more components of their income. After the survey, statistical analysis of the characteristics of households where income is available allows income data to be imputed for households where income data is missing. After imputation, missing income data is reduced to only 3% of households ( see Glossary for more details).
The income information in the report includes the income of the Highest Income Householder and their spouse or partner (where there is one). Income from employment, pensions and benefits and income from other sources is included. The income of other household members is only included if it represents 'other' income for the HIH or spouse, i.e. the other household member contributes to household resources by paying 'dig money'.
The current income information collected through the SHS, is only intended to provide estimates by income band. The survey asks for income only for use as a "background" variable when analyzing other topics, or for selecting the data for particular sub-groups of the population (such as the low paid) for further analysis. The SHS cannot be used as a source of figures on average income or average earnings (See Scottish Household Survey, Methodology 2003/2004 for further details).
Statistical significance
Where reference is made in the text to differences between sub-groups of the sample, these differences have been tested and found to be significant at the 95% confidence limits. 9
All survey data has a degree of error associated with it because it is based on a sample of the population. Any proportion measured in the survey has an associated sampling error, usually expressed as x% at the 95% confidence limits. Technically, all results should be quoted in this way. For example, based on the survey results we can be 95% confident that between 28.7% and 27.3% of adults smoke. However, it is less cumbersome to simply report the percentage as 28% ( See Table 6.54). 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 Appendix 1 provides a simple way to estimate if differences are significant.