What do you see as the most common mistakes that beginning researchers are likely to make with quantitative data analysis? What are the places they are most likely to break down and how do you help them past these? What are the key skills a person should master?
I would say, that a common mistake made by beginning researchers that begin to grasp quantitative analysis, is to try to estimate really complex models. Sure, once you understand multivariate regression, the step from three to 20 variables is not a big one - technically, that is.
I would argue that if a researcher is looking for an association between variables, and this association is not to be found in a 'simple' contingency table, the researcher should be able to provide very good reasons to try to estimate a more complex model. Sure, there are plenty such reasons, but to be able to provide and understand these reasons shows a true understanding of the complexities of multivariate statistics.
So, when unexpected results show up, teach your students to always go back to the simple analysis of data: create frequency tables, contingency tables, and lots of plots of the data. Train them to explicitly think why they would want more complex models. If they can explain, they show to understand these complex models. If they cannot explain, have them think about the assumptions made in all models.
Some of the common mistakes made by beginner researchers in quantitative analysis might include:
1) try to grasp or learn all the statistical / quantitative analyses at one go / in one semester - this might due to the wide syllabus of the quantitative analysis that needs to be covered in one semester like inferential, multivariate analyses etc. Suggesting beginners to go through them / attending the same course again (if the university allows) rounds & rounds so that they really understand & know how to apply them
2) Some beginners might be too focus on / hung up to remember all the statistical formulas - with software like SPSS etc. easily available, they should seek to understand the objective & the application of the analysis instead of focusing on the formulas
3) beside learning the quantitative analysis by itself, the beginners should also start reading empirical / academic articles from relevant journals - so that they know how to apply and understand the conditions to use a particular analysis, understand the prerequisites of the analysis, why this analysis & not that analysis, important outputs that needs to be displayed etc. (this can improve their learning & love for various quantitative analyses)
I think that superficial preparation of the conception of the research what may be the result of superficial knowledge on the researched area. Simply, the beginner doesn't read enough before starting the research.
- Badges
- Science topic