CIS 400 Project ProposalProject topic: How far students from top 100 universities are willing to travel for job aftergraduation.Summary of what we would do:Our sample is the students from the top 100 school in US according to U.S News. We firstrandomly select 50 users that were graduated in each school on the list by using LinkedIn API.By the sample size formulaWhere Z= Z value (e.g. 1.96 for 95% confidence level)p = percentage picking a choice, expressed as decimalc = confidence interval, expressed as decimal (0.04=±4)We get we only need 384 people to get the 95% accurate analyze among 1 millionpeople. We choose 50 people for each school to make it more accurate and avoidunexpected situation.Then by using LinkedIn API, we will gather users’ information about their graduation school andcurrent working place for each user. To further analyze what affects users’ choices, we will alsogather information of users about their major, GPA, internship or work experience, how manyyears after graduation, hometown (native or international?). In dealing with data we get, wewould draw some conclusion about the relation between users’ graduation place and theirworking place.Significance of the idea:By analyze the student’s choice of work city in top 100 Universities, we could predict how farstudents will go for work in different university. We would generate the list of the distance andthe student’s university by increasing order, and create the graph of the relationship betweengraduate school and present working place. Therefore, we could predict how far and wherestudents would work after their graduation according to their school and major.Work PlanLinkedIn PartLinkedin APIFind 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 travelpath for each user. (America only)Step 1: make a table of top 100 US school50 User per schoolschool usersA, userB, ….Step 2: fetch user informationTo learn why users choose their current work place, we may consider and fetch those information aboutusers 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 placeStep 3 :Classification by major, Top five City choiceGoogle Maps PartCalculate distance, Illustration.Step 4:Use Google Maps api for each school location and company location coordinateSchool location coordinate Present work location coordinate distanceStep 5 :Calculate the average distanceSchool name Average travel distance Maximum traveldistance% of people who travelabove averageStep 6:Analyze top five city that students would choose by major and schoolExtra jobs:Use Google API to draw the path that user travels.Data visualization本团队核心人员组成主要包括硅谷工程师、BAT一线工程师，精通德英语！我们主要业务范围是代做编程大作业、课程设计等等。我们的方向领域：window编程 数值算法 AI人工智能 金融统计 计量分析 大数据 网络编程 WEB编程 通讯编程 游戏编程多媒体linux 外挂编程 程序API图像处理 嵌入式/单片机 数据库编程 控制台 进程与线程 网络安全 汇编语言 硬件编程 软件设计 工程标准规等。其中代写编程、代写程序、代写留学生程序作业语言或工具包括但不限于以下范围:C/C++/C#代写Java代写IT代写Python代写辅导编程作业Matlab代写Haskell代写Processing代写Linux环境搭建Rust代写Data Structure Assginment 数据结构代写MIPS代写Machine Learning 作业 代写Oracle/SQL/PostgreSQL/Pig 数据库代写/代做/辅导Web开发、网站开发、网站作业ASP.NET网站开发Finance Insurace Statistics统计、回归、迭代Prolog代写Computer Computational method代做因为专业，所以值得信赖。如有需要，请加QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp
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