Most statistical analyses assume that the data collected are from a simple random sample of the population of interest. However, it’s not always possible or practical to take a SRS, and complex samples can be used to create more efficient or cheaper sampling designs.
read moreIn a recent post we introduced some basic techniques for summarising and analysing categorical survey data. Whilst these methods are a great way to start exploring your categorical data, to really investigate them fully, we can apply a more formal approach.
read moreIt’s important to identify and understand the drivers of key business outcomes. You might want to understand which aspects of your service influence how likely a customer will be to recommend you, for example. A so called key driver analysis can be used to address this sort of question.
read moreWhen conducting research about your customers, patients or products, it's crucial to consider what effect your sample size will have on how valid and reliable your conclusions will be. Larger sample sizes give more reliable results with greater precision and power, but they also cost more time and money.
read moreSurveys often comprise tick-box questions, resulting in what are referred to statistically as categorical data. Analysing categorical data requires the use of a specialist set of statistical tools as they are not normally amenable to the standard tools available for continuous data.
read moreAn interesting pair of polls appeared over the weekend that intended to reflect public opinion on the Government’s policy on Libya. However, it's important to find out what exactly was asked when reading about survey results as the phrasing and structure of a survey question can affect the results.
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