Are there benefits to gaining a strong statistical background?


Psychology is a science that relies heavily on research and the use of statistics to analyze the data collected, whether descriptive or inferential.  Regardless of the way the data is presented, as a statistical procedure or visual representation, it plays a vital role in the progression of hypotheses and the understanding of mind and behaviour.

The usefulness of statistics is largely dependent on the objective of the psychologist and aims of the study.  For example, in a study where the quality and understanding of emotions and feelings regarding an experience are the main focus then numerical statistics are of little use.  In this scenario qualitative data in a non-numerical form would provide a much clearer image of what is desired (Willig, 2008).

A situation when statistics are particularly beneficial is when a psychologist wishes to investigate cause and effect relationships, and to use this information to predict future actions (Gravetter & Wallnau, 2009).  Obviously no form of statistic can accurately predict the future and guarantee this will happen, but it can be used to estimate the likelihood of something occurring again under similar conditions.

A strong statistical background would be made up of various individual statistics, such as the mean and correlation coefficient etc.  These statistics play an important role in influencing what key areas require more research and how hypotheses can be extended to increase our knowledge in that area. K. Gómez and A. Gómez (1984) believed a statistical background was essential to help decide what techniques of research would be more effective for a particular study.

A common use of statistics is for comparison.  How many times have you sat an exam, and after receiving your results wanted to know how everyone else got on to compare? If it wasn’t for statistics it would be very difficult to accurately make this comparison and understand the extent of it. If the majority of people received higher than a grade C, does this mean that just over half have managed this, or a much larger group? By using statistical procedures, such as calculating a percentage, we can construct a more detailed image about the distribution of results of the students.

However, statistics can appear misleading if inadequate background information is given, such as the amount of students who sat the exam in the previous example.  They can often be used to misguide people and to direct people towards a certain thing, when maybe the evidence is not the most substantial.  For example, with many adverts they tell us that 75% of people recommend this product, however if you read the small print its only out of a sample of about 40 people, which in reality means only 30 people actually agree. When the results are from a sample size this small it is hard to generalize to the whole population.

Although statistics are not always the most suitable way to analyze data and draw inferences from it, it is a method that is uniform and is understood by all, regardless of location and language.  It is a simple way of summarising and communicating information to those who wish to investigate it.  However, having a strong statistical background is most beneficial when combined with qualitative research in order to construct a more accurate and reliable representation of what the data shows and means.




4 responses »

  1. Really great post, the final paragraph sums up the points you made well! I agree that qualitative information is best presented in a non-numerical form. Are there any situations where a strong statistical background is not beneficial? Most likely not, but it’s a question worth considering!.

  2. i agree 🙂 statistics are beneficial to everyone in all aspects of society and are especially important in psychological research when choosing how to investigate a research topic and when trying to support or reject a hypothesis, statistics are probably the most beneficial in research. A good knowledge of statistics also proves very beneficial when trying to avoid being sucked in by the media advertising products as many of us are!…This is probably the one that affects us as consumers the most. Awesome blog,you’ve covered a huge range of uses in statistics and how they are beneficial in them aspects 🙂

  3. I also agree, you do need a strong background in order to get the most out of stats. Especially in a course like ours in which a lot of the emphases is placed on us learning as much as we can about stats. But i must say I don’t really agree with the point you make in the 3rd last paragraph. The comparison is right but to what extent?!.. we don’t really use comparisons like that unless it is for comparing with previous research or for 2 variables but for an example like above not really. A better example would of been more appropriate for that point! Over all great blog.

  4. Thank you everyone for your comments. To superfunpsychology, I have to agree that there most probably are few cases where a strong statistical background is not beneficial, provided that the stats are not too heavily relied upon. Sometimes someone sees a significant difference and thinks that this means their research is awesome, when maybe if they look into the rest of the data and info more carefully it might not be so good. To limerickgirl, the comparisons I was referring to mostly meant between variables and between different population groups. If a study was extended so that it was done between different populations aswell as the original study of comparing treatment groups then maybe the populations could be compared to see if the data can be generalised more, and how it differs. Also its used in media. If you think of an Asda advert for example, they use statistics to compare to other shops, saying how theyre cheaper on X amount of products to Tesco, and things like that(possibly not the best example as it doesn’t use percentages, but you get the idea).

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