Each row in CPR.csv corresponds to University data for a given academic year. Assume that this data was collected by the United States Department of Education over 10 academic years (2010 – 2019) to better understand the variability in higher education completion rate (CPR) across 120 Universities, and the factors influencing the completion rate.
Relevant information about data variables is given below:
YEAR: Academic year
INSTNM: Institute name
CITY, STATE, COUNTRY: City, State where University is located in United States
INST_TYPE: Type of Institution – Public or Private
NT_TUT_REV: Net Tuition Revenue per student ($)
INST_EXP: Instructional expenditure per student ($)
AVG_FAC_SAL: Average faculty salary per month ($)
TS: Total students enrolled in the academic year
TS_MEN: Percentage of total students enrolled - Men
TS_WOM: Percentage of total students enrolled - Women
TS_MAR: Percentage of total students enrolled - married
TS_DPEN: Percentage of total students enrolled - dependent
TS_VET: Percentage of total students enrolled - veteran
TS_PT: Percentage of total students who study part time
ST_FI_LO: Percentage of students whose family income is in the range $0-$30,000
ST_FI_M1: Percentage of students whose family income is in the range $30,001-$48,000
ST_FI_M2: Percentage of students whose family income is in the range $48,001-$75,000
ST_FI_H1: Percentage of students whose family income is in the range $75,001-$110,000
ST_FI_H2: Percentage of students whose family income is $110,001+
HL_ED_MS: Percentage of students whose parents’ highest level of education is middle school
HL_ED_HS: Percentage of students whose parents’ highest level of education is high school HL_ED_PS: Percentage of students whose parents’ highest level of education is postsecondary education
CPR: Higher education completion rate for full-time, first-time students (refers to percentage of students who complete their education and graduate)
As a Data Analyst working for the Department of Education, you are required to create the following data visualizations:
1. A visualization (preferably a map) that shows TS and CPR for all 120 Universities.
2. A visualization that answers the following questions:
• Is there a relationship between INST_EXP and CPR?
• Is there a relationship between AVG_FAC_SAL and CPR?
• Is there a relationship between gender ratio and CPR?
• Is there a relationship between TS_PT and CPR?
You are required to demonstrate an application of string parameters in this visualization.
3. 3. A visualization that explores the relationship between student cohort’s family income and CPR.
4. A visualization that explores the relationship between student cohort’s parents’ education and CPR.
5. 5. A visualization that provides comparative CPR analysis among top 10 universities with highest completion rates
All visualizations should be filterable by academic year. Visualizations 1,2,3, and 4 should also be filterable by INST_TYPE.
Finally, prepare two dashboards that could be used as presentation slides for the purpose of presenting insights to the management. In these 2 dashboards, you should explain any two interesting insights gleaned from the above visualizations.
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