The work of a statistics agency does not end when the information provided by respondents has been collected. Turning that information - often in the form of pencil marks on millions of sheets of paper - into reliable statistics of acceptable quality involves a range of activities that take place once the survey has been completed.
Depending on the survey, this can entail seasonal adjustment, where volatility in activity caused by seasonal factors can be smoothed out to reveal better underlying trends.
In a sample survey, weighting of the data collected, so that sample information is made representative of the total population, is always undertaken.
Data is edited to remove inherent improbabilities and errors in collection. In the 1996 population census, we found cases where children below the age of five were reflected as holding tertiary educational qualifications. A woman over the age of 80 was reported as having given birth in the previous year! These were clearly errors, possibly the result of mistakes by field workers.
In some cases, missing information has to be imputed to improve the data quality. Again, I remember cases in previous censuses where the sex of respondents was not provided. If the respondent had given birth to a child, we applied automated editing programmes to impute that the respondent was a woman.
A responsible producer of statistics will indicate to users where and how editing and imputation have been used.
After a survey, the information collected is often subject to other quality assessments and validation processes.
In South Africa, census field work is immediately followed by a post-enumeration survey. This is done by a team independent of those responsible for the original field work, and is designed to quantify the undercount and evaluate the accuracy of information gathered.
Data gathered in two of Statistics SA's sample surveys are now undergoing post-survey validation and verification.
The Community Survey, covering a sample of nearly 280 000 households, is by far the largest sample survey undertaken by Stats SA.
For this reason, post-survey validation is an important mechanism to evaluate the quality and reliability of information collected by field workers.
The information required for this exercise is being collected by field workers, while a separate team of professionals is undertaking the analysis for validation of data quality.
The post-survey validation of the Income and Expenditure Survey (IES) is about to begin as well. To some extent, this is being undertaken because of the general difficulties experienced - globally as much as in South Africa - in collecting data on income and expenditure patterns. Households find it difficult to recall total expenditure by category in a given period, while income is often underreported.
Another reason for this validation is that the IES used an ongoing diary method to collect data for the first time. In 1995 and 2000, it used a single questionnaire asking respondents to recall their expenditures over a 12-month period.
Under the new method, diary booklets were provided to 24 000 households across the country, which explained the information required and how to record it. With ongoing help from Stats SA field workers, each household was asked to record its daily purchases in a specific format enabling the exact nature of the item to be correctly recorded for later processing by Stats SA.
Five interviews were conducted with each household during the reference month. Each household completed one diary a week, or four in total.
While some countries use this method extensively, the IES is the first South African survey to use the diary method. Correctly implemented, it will provide better quality statistics than a questionnaire relying on recall. However, it places considerable demands on both responding households and field workers. For this reason alone, post-survey validation is important to ensure the completeness as well as accuracy of the expenditure data recorded.
To avoid an additional burden on sampled households, information for validation will be collected from Stats SA staff using the same diary method. During August, all staff will keep a diary recording weekly household spending. Patterns discerned in this exercise will assist in evaluating the IES's completeness and accuracy.
Post-survey evaluation, validation and verification can be time-consuming, especially when complex editing rules have to be applied, and new teams of field workers have to return to many respondents. However, Stats SA's commitment to publishing data of appropriate quality necessitates that these additional steps be taken in the statistical cycle.