ASR provides independent statistical services for clients using data sets derived from a variety of sources.
Sampling and weighting
Sampling is the statistical process to determine how many units of information are required to reliably represent the population being surveyed. ASR can determine sample size to produce statistically sound information. Statistical confidence in the survey results depends on how well the data represents the population surveyed. Too small a sample makes the results questionable. But equally, too large a sample is wasteful and unnecessarily expensive. The best balance can be achieved by good sample design. In addition to producing a statistically valid response sample, we can help you determine the most cost-effective sample for your survey needs—whether they are simple, single population opinion surveys, or complex, multi-faceted surveys.
We develop sample frames for complex research projects using a range of sampling techniques. Once data has been collected, it can be compared with known population profiles to determine whether or not the sample results require weighting. Again, ASR can apply a range of weighting methods.
Advanced statistical analysis
ASR has the expertise and tools to produce sophisticated multivariate analysis and statistical modelling of data sets. These procedures include factor, cluster and regression analysis.
ASR can also provide on-line statistical reporting and graphical presentation of data. This service is particularly valuable if you are routinely collecting data from multiple sources and want to keep users up to date with results online rather than through expensive printed reports.
We present the results using a variety of hard copy and online methods, including dashboards.
ASR can provide various forms of validation: at question design stage, at data input stage or when manipulating collected data.
Initial validation can be a combination of face, content and expert validation. ASR can conduct instrument or item validation. Validation determines the degree to which a scale measures what it is supposed to measure. It is a critical requirement of most psychological testing, where ambiguously worded questions can lead to invalid interpretation. ASR can provide item validation procedures to test the validity and reliability of individual scale items.
Data input is usually controlled through software mechanisms. However, this may involve using different collection methods as well. Data output validation involves statistical tests to ensure that data falls within pre-defined limits or benchmarks. This may involve transformation of scores into benchmarks or other formats to meet reporting criteria.
Data cleansing and mining
With our data warehousing capability and our statistical expertise, we can cleanse, combine and analyse data to create new information that will provide your decision-makers with insights for improving your organisation’s performance.
Before using data, it must be tested to ensure that it is valid, reliable and contains no spurious information. Web-collected data can be controlled within our SurveyManager software. But where automatic data validation is not possible, for example open ended questions, or text-based responses where a respondent can enter either a percentage value or a numerical value, it is important to clean data and provide a consistent set of responses.
Data mining techniques can be applied to complex data sets to automate the extraction of hidden predictive information contained in these data. Data mining is an extension of statistical analysis and provides solutions to business decision problems. For example, data mining is a particularly useful when applied to customer relationship management (CRM) data. It can efficiently uncover trends and allow users to build customer behaviour models. These, in turn, can be used to predict customer response to a new product.
ASR can help you design how to mine your data sets. This can be useful if successive sets of information are built over time such as through repeat surveys.