RepGraph provides statistical analysis and interpretation of research data. This may be
research carried out by RepGraph, commissioned by ourselves on your behalf or data
gathered by your organisation. We also conduct data cleansing exercises on a bespoke basis.
How does RepGraph handle data?
Process management, careful planning and consistent cleansing techniques are employed to ensure
good quality data by removing systematic and non-systematic errors. Data
suitability are checked statistically to ensure that meaningful answers are obtainable from the available data.
We often work with large and medium sized, complex datasets that are difficult to
process using traditional applications and techniques. We employ data mining
methods to explore Big Data in search of patterns and/or systematic relationships
between variables, and also to validate findings by applying the detected patterns to
new subsets of data.
RepGraph develops domain knowledge through research and communication with our
clients. This not only assists with data validation but also guarantees that outputs such
as online reports and presentations have the right context and are relevant to the target audience.
Hover over any point to see the waiting list value.
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