Formal Business Memorandum
TO: President of the University
FROM: Head of Department for International Students
DATE: November 3, 2016
SUBJECT: Introducing statistical methods to optimize the University business operations
We have identified new opportunities of using the statistical tools to guide the decision-making in the University marketing, coordination of business operations in the Department for International Students, and also assisting students in choosing Research Internships or Practicum Internships. There is a distinct role of the Department for International Students to use the available data of all international students' information and conduct a statistical analysis to support the decisions, but some of the employees have doubts about applicability of statistical methods to the available data set. The data set currently consists of all international students' information from the school such as name, age, TOEFL score, SAT score, high school, middle school, financial status etc. Here we represent the brief overview of how those methods can be implemented.
Cluster Analysis
Cluster analysis is a statistical tool used to group observations characterized by similar features into smaller groups within the larger population. Cluster analysis may help to partition massive data into smaller groups based on the similarity of their features, can be employed to classify objects and conduct outlier analysis. We can use this tool to identify like-minded student profiles and advice them on the Research Internships or Practicum Internships available at our University. By employing the Cluster Analysis, we can also cluster the first year students and applicants to develop the targeted marketing program (for example, based on the specific features of the most successful cluster we can construct the applicant profile and target those groups).
Multiple Linear Regression
Multiple Linear Regression is another statistical tool that may be employed to guide the decision-making process in the Department for International Students. We can use this tool to identify the key factors influencing the students’ performance, so we can act strategically on students’ performance and achievements. For example, as a dependent variable we might use the students’ achievements during their tuition (average score, research publications, etc), while independent variables can include TOEFL score, SAT score, high school, middle school, financial status, place of birth. Identifying the most significant factors influencing the students’ achievements, we might want to attract students that can be considered promising based on the values of those factors.
As a President of the University you have a critical role in the decision-making processes. We welcome your feedback on this initiative and on how we can best support you in making informed …
