Statistics: the word itself sounds sterile and mathematical, bringing even the most ambitious psych students to tears.  Surely if you ask most psych students why they have decided to major in psychology, more than likely you would get an answer that is rooted in counseling psych, such as “I chose to major in psychology because I want to provide therapy.”  Regardless of what your motivation is to pursue a profession in psychology, statistics is part of most core curriculum of a bachelor’s degree in psychology and can also be found in the peer-reviewed psychological publications that are referenced in upper-level psychology courses.  In other words, there is very little that any aspiring therapists and psychologists can do to avoid taking another “math” course.

Most people consider me a deviant and oddity, an outlier, simply because I enjoy both learning about statistics and teaching statistics.  Do not get me wrong; I was not always part of the dark side of psychology.  I, too, started my undergraduate psych degree thinking that I was going to become a clinician, working with the most abnormal diagnoses, such as schizotypal, bi-polar narcissists.  But, I have grown to appreciate statistics and its elegant approach to making sense of human behavior.

Let me start off by saying that I do not consider statistics a form of math, only because some math does not make sense, like imaginary numbers.  Statistics, in my opinion, makes complete sense because every numerical value has a meaning and a purpose.  In essence, statistics has two primary functions: to examine relationships and to explore differences.  What I mean by that is that you are either investigating if two or more variables have a relationship (e.g., as hours of studying statistics increase, so do students’ anxiety level) or if you are investigating if two or more variables have differences (e.g., attending abnormal psych courses bring psychology students more happiness than attending statistics courses).

Is statistics really that simple?  The answer is no.  There are much more complex rules (i.e., assumptions) that need to be met before you can run an analysis.  But, understanding whether you want to examine either relationships or differences is the basis or all theses, dissertations, and research studies.  In fact, one of the biggest mistakes that I have seen across numerous research studies is researchers using an incorrect statistical test to reject the null the hypothesis.  Notice, that I said researchers and not students.  The reason for that classification is that everyone is prone to making this error, merely because, in the field of psychology, most courses are focused different sub-sections of psychology, not statistics.  And if for some odd reason a researcher had the opportunity to take several statistics courses in their master’s or doctoral program, like most procedural information, “if you do not use it, you lose it.”

Now, is it possible to learn statistics without being a mathematics major?  Yes, it is very possible.  But, it takes a lot of dedication and good mentorship.  The dedication to commit to a topic like statistics is crucial, especially if the material you are trying to learn is not mandatory to learn.  It is quite easy just to let statistics be a memory of the past.  Thus, if you plan on learning statistics, you would have to invest a bit of time to getting bits of information regarding specific analyses that interest you.  The second part of my suggestion is to get a good mentor to help you understand the information you are studying.  Good mentorship is key toward helping you understand complex parts of certain statistical tests.  For example, traditionally, the probability values, better known as the p-value, had been the best indicator to validate whether your analysis rejects the null hypothesis.  A p-value under .05 meant that you found statistical significance and you can confidently reject the null hypothesis because you found a “real” difference or relationship.  Within the last five years, the standards of statistics have become more rigorous, which means that having a p-value under .05 is not enough to establish a significant finding.  Rather, to determine statistical significance, you must meet certain standards across three indicators: the p-value, the effect size, and the confidence interval (Cumming, 2013).  Updates on statistical practices is rarely shared with psychology students, which is why having a good mentor who is knowledgeable in statistics would be helpful.

Being fluent in statistics is very beneficial.  Besides doing well in your statistics course, you are afforded numerous opportunities, such as engaging in student research or assisting a professor in data analyses.  If research is not the route you want to pursue, statistics even has a presence in therapy.  Before therapy sessions, patients are given numerous self-reporting measures to complete.  Statistics are then used to determine the effectiveness of the counseling via pre-post tests.  Also, some therapists use statistics to predict future disorders based on the client’s current diagnosis.

In sum, statistics is not esoteric knowledge nor is it a wicked subject created by warlocks to derail students from becoming psychologists.  With the right attitude and good mentorship, you can amaze your colleagues and professor with the skills and tenacity of Karl Pearson.  Also, take advantage of all of the resources available to you.  Personally, I would not recommend using the textbooks that you were assigned for your statistics course as a resource to learn statistics.  Most of those textbooks are overly saturated with equations and language that is drab and unappealing.  Alternatively, Andy Field, who has a psychology background, has published a few books that explain statistics in a humorous way that is easily digestible.  These books are chalked full of real world examples, hilarious characters, detailed pictures, and covers procedures for statistical programs, such as R or SPSS.  In fact, “Discovering statistics using SPSS” was the first book that I purchased to learn statistics.  Another great resource is “how2stats,” which is a Youtube channel.  how2stats uses annotated videos to describe both the theory and application of statistics.  Similar to Andy Field, how2stats covers how to use SPSS to run complex analyses.

Whether you plan on embracing statistics or not, just remember that your professor has an excellent reason for teaching you statistics.  As the discipline of psychology evolves and becomes more evidence-based, statistics will become both more ubiquitous and standard practice.  Karl Pearson once said that “Statistics is the grammar of science.”  If this is true, then it is crucial for psychologists across all sub-disciplines to know who to communicate with the rest of the scientific community.  I think that Field (2013) eloquently summed up learning statistics when he said, “Statistics is a bit like sticking your finger into a revolving fan blade: sometimes it’s very painful, but it does give you answers to interesting questions” (pg. 2).


Cumming, G. (2013). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. Routledge.

Field, A. (2009). Discovering statistics using SPSS. Sage publications.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage publications.

how2stats. (n.d.). Home [YouTube Channel]. Retrieved from

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Previously, Adolph was a Research Consultant for Pearson’s Research & Innovations Network, spearheading research projects regarding the effects of rapid feedback on standardized testing. His current research focuses primarily on evaluating moderating factors that reduce the behaviors associated with the acquisition and transmission of STIs and HIV among at-risk populations.


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