Collecting, analyzing, and reporting with data can be daunting. The person SAGE Publishing — the parent of MethodSpace — turns to when it has questions is Diana Aleman – editor extraordinaire for SAGE Stats and U.S. Political Stats. And now she is bringing her trials, tribulations, and expertise with data to you in a monthly blog, Tips with Diana. Stay tuned for Diana’s experiences, tips, and tricks with finding, analyzing and visualizing data. View Diana’s blog HERE.
If you’ve visited CNN, NPR or the New York Times in the past few weeks, you may have heard about the current teacher strikes in certain states demanding higher salaries. Oklahoma, Kentucky, West Virginia, and Arizona are among the key states where teachers are protesting what they believe to be unfairly low salaries compared to their colleagues in other states. When considering teacher salary data, it is interesting to examine how these numbers have changed over time and how they vary by state.
Overall, average public school teacher salaries increased by nearly 60 percent between 1995 and 2017. However, by using the data set above to calculate this change by state, it’s clear that some states have experienced slower salary growth than others. For instance, teacher salaries in Oklahoma, Arizona, and West Virginia have increased by 38 percent, 48 percent, and 43 percent, respectively, whereas salaries in states such as New York have risen as much as 68 percent in the same time period.
As with any analysis, it is important to consider external factors that may influence the real-world implications we observe in data. When comparing data such as salaries among states, factors such as regional cost of living and state averages must be included. It’s unlikely that the average cost of living is the same between Oklahoma and Manhattan, for example, which may account for the differences in salary growth. At the same time, data can never tell the entire story, and news stories reporting teachers who work multiple jobs to pay rent illustrate that there is a problem beyond just differences in cost of living.
Therefore, this case illustrates the intersection between a data set, external factors, and real-world implications. While it may be easier to draw conclusions based on numbers alone, it is crucial to contextualize an analysis by considering underlying factors and then examining their impact on society. Working with both hard data and first-hand news articles is a good first step to getting closer to the full story for any data challenge.