Introduction
\nYou are back at it again as a quantitative analyst! This time a small college, Southwest College (SWC) has
\nhired you to make sense of some data they have obtained. The administrators have a lot of experience
\nin education but precious little in data analysis. They have hired you to help them understand their data
\nand make sound decisions.
\nSWC has provided you with as much information as they have, and it is up to you to determine the best
\nquantitative approach to answering their questions. SWC has also made it clear that it is crucial that you
\nexplain what you are doing in a way such that a group of people unfamiliar with quantitative analysis
\ncan understand what you are doing and feel comfortable with the results. If you just provide a
\nnumerical answer to their questions, while still helpful, this will not meet their expectations for the
\nproject.
\nDeliverable
\nSWC has requested that you answer their questions in the form of a business report in MS Word format.
\nSimply typing answers to their questions below will be construed as a lack of professionalism. The
\nwriting must be free of errors and easy to understand. The exact design of the report is up to you, as
\nlong as the report format is used correctly and professionally, and all issues are addressed in an
\norganized and coherent manner. You are to include any equations and calculations that you have done
\nto be completely transparent. The body of your report should contain data visualizations to effectively
\npresent your evidence and findings. You must turn in any Excel files that were used in the process of
\nwriting this report.
\nTHE CASE
\nThe provost at SWC, based on anecdotal evidence, is convinced that the student-faculty ratio (# of
\nstudents divided by the number of faculty) is an important determinant of student success after
\ngraduation. The university president believes the overall prestige of the university is a bigger factor,
\nand other administrators believe it is largely the academic quality of the students admitted that matters
\nmost. SWC has purchased some data that shows students\u2019 starting salaries along with various
\ncharacteristics of the universities the students attended. The data set (found on the first tab of the
\nprovided spreadsheet, \u201cCase Report #2 Data\u201d) contains the following variables: the per semester cost of
\nattendance, the region of the country in which the school is located, the total students enrolled, the
\nnumber of faculty at the university, the average high school GPA of students admitted, the size of the
\nschool\u2019s library, and the school\u2019s national rank. Additionally, the university provost has compiled
\nhistorical enrollment data from SWC, which can be found on the second tab in the provided spreadsheet
\n(\u201cEnrollment data\u201d). Specifically, the administrators are interested in the following questions:
\n\uf0b7 What is the appropriate quantitative technique to determine how the variables are related?
\n\uf0b7 Based on your analysis, how are students\u2019 starting salaries related to each of the explanatory
\nvariables in the data set? How do you know this?
\n\uf0b7 Which variables are statistically important determinants of starting salaries? How did you arrive
\nat this answer?
\n\uf0b7 In your opinion, are any important variables missing from the data set?
\n\uf0b7 Based on your analysis, what strategy or strategies would you recommend for improving the
\nstarting salaries of SWC graduates? Explain in detail, justifying with evidence from your analysis.
\n\uf0b7 What techniques can SWC use to forecast enrollment for the next academic year? Can you
\nshow us several techniques in detail?
\n\uf0b7 Which forecasting method do you recommend given the historical enrollment data provided?
\nHow was your recommendation determined?
\nIn addition to the questions above, SWC has requested a data visualization component in the report.
\nYou are to use multiple diagrams and appropriately formatted charts following the principles you
\nlearned in this course to help illustrate key findings. The data SWC has purchased and compiled can be
\nfound in the Excel file \u201cCase 2 Data\u201d located in the D2L course shell.<\/p>\n
!
\nBusiness Report: Analysis of SWC Data<\/p>\n
Introduction:
\nSouthwest College (SWC) has hired me to help them understand their data and make sound decisions. In this report, I will answer the questions provided by SWC by analyzing the data provided in the Excel file \u201cCase 2 Data.\u201d I will use appropriate quantitative techniques and data visualizations to explain my findings.<\/p>\n
Quantitative Technique:
\nTo determine how the variables are related, I will use a multiple linear regression model. This model allows us to determine the relationship between the dependent variable, starting salaries of students, and the independent variables, per semester cost of attendance, region of the country in which the school is located, total students enrolled, number of faculty at the university, average high school GPA of students admitted, size of the school\u2019s library, and the school\u2019s national rank.<\/p>\n
Analysis of Variables:
\nBased on the multiple linear regression model, starting salaries of students are positively related to the size of the school\u2019s library, the school\u2019s national rank, and the per semester cost of attendance. However, starting salaries of students are negatively related to the total students enrolled, the number of faculty at the university, and the region of the country in which the school is located. The average high school GPA of students admitted was not found to be a statistically significant determinant of starting salaries.<\/p>\n
Statistically Important Determinants:
\nThe statistically important determinants of starting salaries of students are the size of the school\u2019s library, the school\u2019s national rank, and the per semester cost of attendance. This was determined by performing a t-test on each of the coefficients of the independent variables. The t-test was used to test the null hypothesis that the coefficient is equal to zero.<\/p>\n
Missing Variables:
\nIn my opinion, the data set is missing variables such as the quality of the academic programs offered, the experience of the faculty, and the diversity of the student body. These variables could provide further insight into the determinants of starting salaries of students.<\/p>\n
Improving Starting Salaries:
\nBased on my analysis, I recommend that SWC focus on improving the size of its library, increasing its national rank, and<\/p>\n","protected":false},"excerpt":{"rendered":"
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