Final answer:
The question involves updating the statistics of a dataset with a new data point and recalculating the linear regression equation to reflect this change. This type of analysis is common in statistics, a branch of mathematics concerned with the collection, analysis, interpretation, and presentation of masses of numerical data.
Step-by-step explanation:
The subject of this question is Mathematics, specifically focusing on statistics and regression analysis.
The student is asked to incorporate a new data point of 2013 with an enrollment of 2250 students and analyze the new statistics.
This requires updating the dataset and recalculating the relevant statistical measures, which may include mean, median, standard deviation, and the linear regression equation.
An essential part of this question involves creating or updating a linear regression equation, which models the relationship between time and student enrollment.
The student is expected to use the new data point to find the best-fit line that represents this relationship accurately. This might involve calculating the slope and y-intercept of the least-squares regression line with the updated dataset.
It's important to note that this updated analysis aims to yield a newer version of the regression equation possibly similar to the one provided in the example, which is y = -355.19 + 7.39(73) = 184.28 or ŷ = -173.51 + 4.83x.
Once the new regression equation is computed, predictions about future enrollments can be made more accurately.