experiences collecting and analyzing data with statistical methods, familiar with R and SAS programing, great knowledge of experiment design, sampling techniques and documents management. strong skills in communication, group-working and work-planning.
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President of Chinese students' and scholars' association
3.7 GPA
Coursework in practical statistical models, data analysis 1, 2, 3, statistical software and data analysis, introduction of probability theory, statistical inference, time series analysis, survival analysis, experimental design, current development in statistics.
SAS advanced license
Projects:
A.
Time: from 2014 January to 2014 Match
Title: the relationship between the mathematical grade of the seventh grade and grades from primary school.
Brief process: use linear model to fit transformed variables from the data after getting rid of useless columns, choose the most significant variables to form the final model based on persuasive diagnostic values.
Achievements from the project:the mathematical grade of the seventh grade is significantly influenced by the reading, counting and logistic ability at the first and second grade in the primary school.
B.
Time: from 2014 May to 2014 August
Title:bike rental prediction
Brief process: construct the regression model use different statistical method, find the most powerful model decided by finding the least error rate, and decide which variables significantly enough to build the model.
Achievements from the project: use Lasso to make the regression, it gives the least error rate and use the almost original data set, it saves a lot of time to deal with the original data set.
C.
Time:from 2014 September to October
Title: Classify Song Release Period
Brief process: construct the classification model to classify a specific song into the year before or after the year 1986 based on 90 attributes of a single song and 6480 songs.
Achievements from the project: use the Multivariate adaptive regression splines to build the model and based on the final classification model, we can conclude that if the song is from before or after on 1986 depends mostly on the artists who create them, secondly on properties they tagged by famous music website and finally on properties of their track.
D.
Time: from 2014 November to 2014 December
Title: predict the lightening strikes in July based on the records from January to June.
Brief process: first cluster the original data based on the lightening strike records and the moisture records with the method of K-mean and Hierarchical method. Second use different statistical method like Boosting, Random Forest, Ridge, Lasso, NNET, CART, SVM to find the best model to predict the strikes will happen.
Achievements from the project: we use the K-mean clustering method and based on the moisture data to form the cluster and use the neural network is a better way for our prediction to get a smaller MSE, and lightning strike have direct relationship with the soil moisture level and the climate indices.
E.
Time: from 2014 November to 2014 December
Title: predict the daily stock price of Netflix Inc. Based on historical daily price records.
Brief process: use GARCH model to fit the transformed data and finally choose the GARCH plus ARMAR model to make the forecasting.
Achievements from the project: from the model we can find that there is a up trend in the future about this stock and this is a appropriate time to buy this piece of stock.
Main tasks of this job:
1.Collect, enter and analyze stock prices: collect useful data and enter them into the database in a correct classification way, use statistical methods to analyze them based on R programming.
2.Predict the future trend of different stocks and divide them into different category: use time series methods to predict the trend
3.Write summary report: use statistical methods to analyze data with R and write the performance evaluation report based on quantitative facts.
4.Customer service: answer the phone call and solve customers' problems and do the reception job at the front table. Also offer the instruction about stocks and how to choose them to new clients.
5.design the questionnaire and the get the feedback
Main tasks about the job:
1.data collection and entering: collect financial data and classify them into the correct table and items.
2.Write summary report: use statistical methods to analyze data with R and write the performance evaluation report based on quantitative facts.
3.Customer service: answer the phone call and solve customers' problems and do the reception job at the front table.
4.inventory control: keep record of the number of materials and keep track of the way they out and in.
5.arrangement the business trip: book the hotel, arrange the schedules for each day, keep track of the budget of the business trip.
Main tasks about the job:
1.data collection and entering: collect financial data and classify them into the correct table and items.
2.Write summary report: use statistical methods to analyze data with R and write the performance evaluation report based on quantitative facts.
3.Customer service: answer the phone call and solve customers' problems and do the reception job at the front table.
4.Meeting preparation: prepare documents need in the meeting, make sure all the participants can come, prepare PowerPoint slides and arrange the meeting room.
5.Introduce production to customers: introduce financial products which the most suitable to the client and persuade them to buy.
1.merit of certificate award for excellent grade which is top 10%
Time: the spring semester of 2014
2.merit of certificate award for excellent performance in the position of the leader of executive department of the Chinese students and scholars association in the university of Missouri.
Time: the Fall semester of 2014
3.merit of certificate award for excellent performance in the position of vice president of the Chinese students and scholars association in the university of Missouri.
time: the Fall semester of 2014-2015
4.Merit of certificate award for excellent performance in the position of president of the Chinese students and scholars association in the university of Missouri.
time: the spring semester of 2015
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