Analysis of Business Week MBA and Undergraduate Business Program Data
Research questions
With this data set, the following research questions will be explored:
Does the cost of tuition show a relationship with the starting salaries in MBA degree graduates?
Does the cost of tuition show a relationship with the starting salaries in undergraduate business degree graduates?
What is the most prevalent starting salary for MBA degrees?
What is the most prevalent starting salary for undergraduate business degrees?
Is there a difference between median starting salaries for MBA graduates and undergraduate business degree graduates?
Does the cost of tuition show a relationship with the percent of MBA graduates with job offers?
Is there a relationship between tuition amount, graduate’s starting salary, and Business Week ranking for MBA programs?
Methods
The excel spreadsheet, Business Week MBA and Undergraduate Data, was imported into Jupyter Notebook and the following steps were applied:
The Pandas library was imported:
import pandas as pd
The MBA-specific data was made into the mba_data Pandas dataframe:
mba1 = pd.read_excel('BW_MBA_data (1).xlsx')
mba1.head()The columns of the dataframe were explored to see what the mba_data contained:
mba_data.head()
The Seaborn library was imported:
import seaborn as sns
The Matplot library was imported:
import matplotlib.pyplot as plt
Exploratory data visualization was completed with the research question in mind:
sns.histplot(data=mba_data, x="Starting_Salary")
sns.set_theme(style="whitegrid")
# Draw a scatter plot while assigning point colors and sizes to different
# variables in the dataset
f, ax = plt.subplots(figsize=(6.5, 6.5))
sns.despine(f, left=True, bottom=True)
sns.scatterplot(x="Tuition", y="Starting_Salary",
palette="ch:r=-.2,d=.3_r",
sizes=(1, 8), linewidth=0,
data=mba_data, ax=ax)sns.set_theme(style="whitegrid")
# Draw a scatter plot while assigning point colors and sizes to different
# variables in the dataset
f, ax = plt.subplots(figsize=(6.5, 6.5))
sns.despine(f, left=True, bottom=True)
sns.scatterplot(x="Annual Cost", y="Median Starting Salary",
palette="ch:r=-.2,d=.3_r",
sizes=(1, 8), linewidth=0,
data=ug_data, ax=ax)
Findings
From the histograms generated in Seaborn, we can conclude that the starting salary for MBA degrees are higher and are more varied than that of undergraduate business degrees, with the most prevalent starting salary for MBA degrees being $90,000 (Figure 1) and the most prevalent starting salary for undergraduate degrees being $50,000 (Figure 2) -- which is an 80% increase in earnings.
The data shows a positive correlation between higher tuitions and higher starting salaries for both MBA and undergraduate degrees (Figures 3 and 4).
For MBA degrees, there was a positive correlation between higher tuition and the percent of the program’s graduates receiving more job offers (Figure 5).
In addition, MBA programs with the highest Business Week rankings also showed a positive correlation with the highest starting salaries and tuitions (with a few outliers with tuitions as low as $40,000 -- Figure 6).
Conclusion of Findings
Based off the visual analysis of the data, we can conclude that higher tuition means that there are more resources available for students to succeed, which is evident in higher starting salaries and more job offers.
More resources may also mean that Business Week will give the program a higher ranking since there is a relationship between higher tuitions and rankings. We can also conclude that starting salaries for graduates of MBA programs are higher than starting salaries for graduates with just an undergraduate business degree.
