The Importance Of Caution And Prudence On Quantitative Data Analysis

1715 Words Sep 25th, 2015 7 Pages
Pryjmachuk, S., & Richards, D. (2007). Look before you leap and don 't put all your eggs in one basket: The need for caution and prudence in quantitative data analysis. Journal of Research in Nursing, 12(1), 43-54. doi:10.1177/1744987106070260

When doing research and using quantitative data analysis in the psychological field, it is not uncommon for mistakes in procedure to be made, nor is it uncommon to mishandle data, albeit typically not purposely. Pryjmachuk and Richards (2007) address this in their article meant primarily for researchers and reviewers, but students could gain a wealth of knowledge from this article as well as this article stresses the importance of caution and prudence when utilizing quantitative data analyses. Typically when doing research a procedure evolves that is rather common. We state out hypothesis, collect the data and enter it into a computer application programmed for statistical analysis, run specific statistical analysis to gain the output we are looking for, and we examine the outputs of the application looking for p-values that are statistically significant (typically at least the 5% level). We of course look for significance because this indicates something that may have been discovered that may be able to be published. Pryjmachuk and Richards (2007) counter that we may depend too much on p-values, as well as a failure to examine the raw data prior to running an analysis on it. They assert that this is not uncommon in health and…

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