Psychology and a Career in Analytics
Over the years, many people have asked me why I became a data professional. They assume it’s odd given that I graduated with a bachelors degree in psychology. The truth is that psychology teaches a well rounded application of statistical analysis. It’s a practical application of analytics that requires careful planning and critical thinking. Psych students learn important lessons about decision making and persuasion which translate well to the world of business analytics. I’d like to answer the question that has been asked countless times, and explain why a psychology degree is relevant to a career in data.
Learn How to Ask Questions Based on Existing Data
While studying psychology, students will be required to conduct several experiments from start to finish. One of the hardest parts of this process is coming up with a hypothesis, which is essentially a prediction based on existing evidence. What I learned from my education is that the good answers require the great questions. And great questions require a good understanding of the underlying context. The skills of summarizing relevant information and summoning a question for analysis are critical for a high-functioning business analyst. These skills will be implemented in a practical setting, which will help any new psychology graduate in the world of analytics.
Statistics, And Lots Of Them
Psychology, along with many other disciplines, is reliant on proper statistical comprehension. One must learn to decipher whether results are meaningful or meaningless. This is important when gathering information for business analytics; sifting through tons of data, finding what’s most important, and then identifying a clear path forward.
Most business decision makers are more interested in the implications of a t-test rather than the t-test itself. Psych students will learn statistical comprehension, allowing them to understand the true meaning of their results.
However, psychology students will also learn the foundations of data, like how variables can be classified into 4 levels of measurement, interval, ratio, nominal, and ordinal. It’s a fundamental understanding of data as it applies to statistics. Business analysts use this knowledge all the time when constructing charts and graphs with varying types of data.
In my education, I gained consistent experience in using advanced statistics software like SPSS. SPSS is a statistical software suite that facilitates advanced analytics. I learned how to apply techniques like t-tests, ANOVAs, and pearson correlations. These techniques can be applied directly to the business world when testing the effectiveness of marketing campaigns, or anytime you need to compare the results of two groups given differing interventions.
Presenting Your Evidence
After conducting the experiment, gathering the data, and running the appropriate statistics, it’s now time to present your argument. Students will learn how explain the importance of their paper, making it interesting while summarizing the research they’ve done. It’s important to be persuasive while not overstepping the limitations of the methods and the reality of the results. And finally, no matter the outcome of the experiment, the student must persuade the reader toward a meaningful and truthful conclusion. Many of these skill translate very well to the process of creating and presenting a convincing argument to business leaders.
Understanding Biases
There are many biases that influence our ability to view data and information. These biases are an important part of the psychology education. I’d like to quickly explore how a few of them influence the role of a business analyst..
Availability Heuristic: The information you use to make decisions is only a small portion of the total relevant information. This bias is highly applicable to data-driven decision making. A good business analyst knows to broaden their scope of data.
Anchoring Bias: The tendency to rely on information you heard early on in the decision-making process. When presenting an analysis, it’s critical that the audience walks away with your intended message, so understanding anchoring bias helps construct your argument properly.
Hot Hand Fallacy: The assumption that a string of successful results indicate continued success. Sometimes, analysts must sometimes be the bearers of bad news by telling the company that the current high revenues may not be reflective of the future. This bias can help confront and explain hard truths.
Confirmation Bias: When gathering information, people may seek out information that is consistent with their beliefs. This will help analysts avoid cherry-picking evidence and instead perform an analysis that questions their expectations.
Conclusion
Psychology teaches how to apply statistics to real world data, synthesize information for decision making, and present results in a provoking manner. I personally use all of these skills in my career as a data professional, and they are more valuable than learning how to use SQL or Excel. I believe that recruiters should keep an open mind toward psych students when hiring for data analyst roles, and graduates should understand how to best answer the question “why do you want to work in analytics after studying psychology?”
