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Statistics is important when it comes to understanding data… but is it essential? Is it all that is needed in order to fully understand the extent of the data been given, or are there other things that outweigh the importance of the statistical values? When data is collected it is automatically assumed that an output will be generated in order to see whether the ‘P’ value supports the hypothesis or the null hypothesis, but should the background reading into the data be more important, should understanding why the data has been generated be more important than the actual P value?

Statistics makes it simple to understand the bare face of data, to understand whether or not the experiment has been successful. Statistics tell a story in simple terms, this is through tables and graphs. The visible data makes it easy to determine what they actually mean, by looking at a produced graph, things like correlation can be easily spotted. This can then make it easy to see if one variable has caused or affected another variable, or whether the two are simply unconnected.

Even though statistics makes it easy to determine data and to visually compare elements, I do not see it to be the absolute essential to completely understanding data. I believe other elements are also important, such as reading into why the data may have been produced, or whether there has been other extraneous variables which has effected the data output which may have not previously been thought about, also whether changing the way the experiment has been carried out could change the data in order for it to support the hypothesis previously set.

To conclude I believe statistics to be partially important when it comes to understanding results, but I do not see it as the sole compartment when it comes to being data literate.


Comments on: "Do you need statistics to understand your data?" (4)

  1. true statistic is a phenomenal concept to analyse data,and its use is spread across all disciplines specially for research purpose.

  2. I understand what you are saying but don’t you think statistical analyses are important in order to generalise, check significance and also errors and validity in your data? Yes visual graphs are easy to understand and look at, but they do not show us in detail validity or significance and as Psychologists we need to be able to apply results to real world but can we do this without statistics checking and analysing the results in more depth.

  3. After reading through this weeks blogs and comments and things, i realised i may have actually missed a few things out of my blog. I do agree that as psychologists we need to analyse the data more thoroughly as psychologists so that we have set data and numbers to make it applicable to the real world with hard evidence, and that this can then be put into graphs and tables for the wider population to understand in a way that they may find acceptable.

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