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How to Analyze Quantitative Data

Analysis of quantitative data in all studies calls for the application of similar general principles whether the study is aimed at children or at adults. Any data analysis aims to figure out the trends, patterns and recurring themes in the data. However, when this data is of a quantitative nature, certain expertise is required for its analysis.

With new possibilities in statistical analysis opening up due to improvements in computer programmes, new opportunities have opened up for researchers to undertake complicated analytical tasks.

But this development in technology comes with two major drawbacks, the first one being the lack of questioning skills in computers which are machines and do not understand if it sensible to actually perform all the calculations, and the second problem being that complicated statistical analysis cannot be understood by most people.

To make this complicated process simpler, follow these ten simple tips to understand the analysis task that is required of you and cater to the audience that will understand the analysis:-

  • The primary raw material that will be used for the analysis is data, so it’s best if you get comfortable with its careful handling.
  • Data has to be clearly understood and thoroughly explored as it is difficult to handle recoding or computing data without making any errors.
  • Results are best displayed in graphical form that will clearly bring out the implications and meaning of the undertaken study.
  • Validity of the results has to be countered by replicating the research in new settings and using new samples.
  • It is imperative to keep track of the difference between effect size and significance of the statistics.
  • Equally important is to remember the difference between substantive significance and statistical importance.
  • Statistics do not speak for themselves, so it is wise not to use endless tables and graphs to make your point. Present the analysed data in the form of an argument that is for or against a particular point of view.
  • Avoid the confusion created out of complex statistics but keeping it simple at all points during the analysis.
  • Take advice of other researchers and colleagues to strengthen your findings, sharpen your arguments and aid in error detection, if any.
  • Perfect research is a myth. Research tends to be more on the complicated and difficult side of expectations, leading to weaker and/or controversial results at the end of the analysis process.

Impetus Research is one of the pioneers in the field of analyzing quantitative data and has had huge success with their techniques and analysis of quantitative data. Check out their services on http://www.impetus-research.com/ and let us know your tips for successful analysis of quantitative data in the comments below.