In this report, we will try to analyze academic program trends in the United States by extracting google searches between 07-2018 and 08-2020. Then, we will implement a forecasting procedure with R language, based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality. First, we can check the google searches for “Nursing Programs” searches:
Then, we do the same for “Technology Programs” searches:
Additionally, to display a better comparison chart, we will extract searches for another type of medical school programs “Technician Programs”.
Now, Let’s summarize the searches per each category in order to have a clearer vision of what we’re looking at:
Finally, we can see that the results are even clearer when they are shown together according to academic program type. Using the information from the last 2 years, we will attempt to predict internet searches per academic program type for the next year. In order to do this, we implement a forecasting procedure with R language, based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects: