Seven Reasons for Psychologists to Pursue Advanced Quantitative Training

• You are limited by the analytic tools you possess - Data analytic tools and theoretical innovation are complementary: Learning newer, more sophisticated analytic tools expands the way you can think about questions. Try to imagine designing a house without a ruler or compass, or actually building a house without a level. The tools you have impact your output; better tools produce better outputs. 
• Reality is complex - It goes without saying that behavior and mental processes are complex, and psychological scientists aim to understand and model this complexity. Sophisticated analytical tools get you closer to modeling our multivariate and hierarchical world. Since many variables operate within and outside of people, it makes sense to model relationships among multiple variables simultaneously. Multivariate analysis of covariance (MANCOVA), path analysis, and structural equation modeling are among the many tools useful for this purpose.
• A conclusion is only as good as its statistical analysis - Statistical tests and models are accompanied by assumptions, and these assumptions are violated more often than we would like. If assumptions are violated, our conclusions are more or less useless: garbage in, garbage out. Advanced, or less conventional, analytic tools typically allow more flexibility in handling and circumventing the assumptions of conventional analyses. When issues of data distribution arise, nonparametric statistics are your friend. 
• Learning now promotes learning later - Without continued practice, it is unlikely that you will retain everything you were taught in an advanced quantitative course. However, the bulk of this education is about learning how to learn. The introduction and initial exposure provide you with the knowledge to read articles, chapters, and entire books later on your own. Your courses should reinforce good data habits as well. In other words, advanced quantitative training will give you “legs to stand on” when you need to learn a new skill or figure out how to best analyze a dataset. Expanding your formal quantitative training will make you a more independent scholar.
• Advanced analytic tools encourage research productivity - We do not always have the resources to collect large amounts of data. If you find yourself at a college or university with fewer resources for data collection, more sophisticated data analytic tools can help you stay active in research. Many organizations (e.g., Pew Research Center, General Social Survey) provide free access to large and longitudinal datasets. Using advanced analytical tools (e.g., structural equation modeling, multilevel modeling, and latent growth curve modeling), researchers can efficiently test multifaceted hypotheses without collecting data.
• You can be a better consumer of research - I already discussed the benefits of advanced quantitative training for producers of research, but this training will also make you a better consumer of research. The most common types of publication in psychological science are empirical journal articles, and you should not only read them but should be able to understand them. 
• Being savvy with analytical tools will make you a desirable colleague and collaborator - It should not come as a surprise that academic psychologists with sophisticated analytic tools are more marketable. We all want colleagues in our department who can explain techniques, teach advanced methods courses, and provide feedback and advice regarding data analysis. 

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