CIS 400 Project Proposal
Project topic: How far students from top 100 universities are willing to travel for job after
graduation.
Summary of what we would do:
Our sample is the students from the top 100 school in US according to U.S News. We first
randomly select 50 users that were graduated in each school on the list by using LinkedIn API.
By the sample size formula
Where Z= Z value (e.g. 1.96 for 95% confidence level)
p = percentage picking a choice, expressed as decimal
c = confidence interval, expressed as decimal (0.04=±4)
We get we only need 384 people to get the 95% accurate analyze among 1 million
people. We choose 50 people for each school to make it more accurate and avoid
unexpected situation.
Then by using LinkedIn API, we will gather users’ information about their graduation school and
current working place for each user. To further analyze what affects users’ choices, we will also
gather information of users about their major, GPA, internship or work experience, how many
years after graduation, hometown (native or international?). In dealing with data we get, we
would draw some conclusion about the relation between users’ graduation place and their
working place.
Significance of the idea:
By analyze the student’s choice of work city in top 100 Universities, we could predict how far
students will go for work in different university. We would generate the list of the distance and
the student’s university by increasing order, and create the graph of the relationship between
graduate school and present working place. Therefore, we could predict how far and where
students would work after their graduation according to their school and major.
Work Plan
LinkedIn Part
Linkedin API
代做CIS 400作业、代做Project Proposal作业
Find the connection between user’s graduation place and present working place.
Main goal: find the average distance people would travel to find a job. Use google maps to draw a travel
path for each user. (America only)
Step 1: make a table of top 100 US school
50 User per school
school usersA, userB, ….
Step 2: fetch user information
To learn why users choose their current work place, we may consider and fetch those information about
users as follows: major, GPA, internship or work experience, how many years after graduation,
hometown(native or international?).
In addition, we may also consider the weather of related place.
User ID: Graduation School Current working place
Step 3 :
Classification by major, Top five City choice
Google Maps Part
Calculate distance, Illustration.
Step 4:
Use Google Maps api for each school location and company location coordinate
School location coordinate Present work location coordinate distance
Step 5 :Calculate the average distance
School name Average travel distance Maximum travel
distance
% of people who travel
above average
Step 6:
Analyze top five city that students would choose by major and school
Extra jobs:
Use Google API to draw the path that user travels.
Data visualization
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