Xiaoqing Zhu is a Ph.D. candidate in Statistics at Michigan State University, advised by Dr. Hira L. Koul. She received her B.S. in Mathematics and Physics from Tsinghua University in Beijing, China. Her research focuses on goodness-of-fit testing, time series analysis, and measurement error models. She has worked as a research assistant at MSU and Tsinghua University and has published papers in peer-reviewed journals.
Measures of Descriptive statistics and Inferential statistics MeganShaw38
The presentation will walk you through descriptive and inferential statistic measures, including a simple scenario, key measures and applications of descriptive and inferential statistic's.
This is a proposal of Research Topic ( Student performance prediction) . DUET CSE 15 Batch.
http://www.duet.ac.bd/department/department-of-computer-science-engineering/
Semantometrics: Towards Fulltext-based Research Evaluationpetrknoth
Over the recent years, there has been a growing interest in developing new scientometric measures that could go beyond the traditional citation-based bibliometric measures. This interest is motivated on one side by the wider availability or even emergence of new information evidencing research performance, such as article downloads, views and twitter mentions, and on the other side by the continued frustrations and problems surrounding the application of citation-based metrics to evaluate research performance in practice.
Semantometrics are a new class of research evaluation metrics which build on the premise that full text is needed to assess the value of a publication. This talk will present the results of an investigation into the properties of the semantometric contribution measure (Knoth & Herrmannova, 2014). We will provide a comparative evaluation of the contribution measure with traditional bibliometric measures based on citation counting.
Quantitative CV-based indicators for research quality, validated by peer reviewNadine Rons
Rons, N. and De Bruyn, A., POSTER presented at the 11th International Conference of the International Society for Scientometrics and Informetrics. CSIC, Madrid, Spain, 25-27 June 2007
Measures of Descriptive statistics and Inferential statistics MeganShaw38
The presentation will walk you through descriptive and inferential statistic measures, including a simple scenario, key measures and applications of descriptive and inferential statistic's.
This is a proposal of Research Topic ( Student performance prediction) . DUET CSE 15 Batch.
http://www.duet.ac.bd/department/department-of-computer-science-engineering/
Semantometrics: Towards Fulltext-based Research Evaluationpetrknoth
Over the recent years, there has been a growing interest in developing new scientometric measures that could go beyond the traditional citation-based bibliometric measures. This interest is motivated on one side by the wider availability or even emergence of new information evidencing research performance, such as article downloads, views and twitter mentions, and on the other side by the continued frustrations and problems surrounding the application of citation-based metrics to evaluate research performance in practice.
Semantometrics are a new class of research evaluation metrics which build on the premise that full text is needed to assess the value of a publication. This talk will present the results of an investigation into the properties of the semantometric contribution measure (Knoth & Herrmannova, 2014). We will provide a comparative evaluation of the contribution measure with traditional bibliometric measures based on citation counting.
Quantitative CV-based indicators for research quality, validated by peer reviewNadine Rons
Rons, N. and De Bruyn, A., POSTER presented at the 11th International Conference of the International Society for Scientometrics and Informetrics. CSIC, Madrid, Spain, 25-27 June 2007
Current CV as of March 15, 2014
PhD Candidate, Epidemiology
University of North Carolina at Chapel Hill
Expected Graduation May 2015
Dissertation: Military Service, Deployments, and Exposures in Relation to
Amyotrophic Lateral Sclerosis Etiology and Survival
MPH Public Health 2010
BS Statistics 2008
Brigham Young University
Primary Research Interests: Occupational, Environmental, and Neurologic Epidemiology
Sample of slides for Statistics for Geography and Environmental ScienceRich Harris
A sample of the slides available to support the teaching of the textbook Statistics for Geography and Environmental Science by Harris & Jarvis (2011). For further information see www.social-statistics.org
How do Scholars Evaluate and Promote Research Outputs? An NTU Case Study
Authors: Han Zheng, Mojisola Erdt, Yin-Leng Theng
Workshop Website: http://www.altmetrics.ntuchess.com/AROSIM2018/
Statistics for Geography and Environmental Science:an introductory lecture c...Rich Harris
A sample of the instructor's resources to support the textbook Statistics for Geography and Environmental Science. Further information at www.social-statistics.org
SPSS Presentation. topics include general concepts of statistics, basic concepts of SPSS, Variables, types of variables, data and its types, sources of data,four windows of SPSS, viewer window, output viewer. results etc..............................
Current CV as of March 15, 2014
PhD Candidate, Epidemiology
University of North Carolina at Chapel Hill
Expected Graduation May 2015
Dissertation: Military Service, Deployments, and Exposures in Relation to
Amyotrophic Lateral Sclerosis Etiology and Survival
MPH Public Health 2010
BS Statistics 2008
Brigham Young University
Primary Research Interests: Occupational, Environmental, and Neurologic Epidemiology
Sample of slides for Statistics for Geography and Environmental ScienceRich Harris
A sample of the slides available to support the teaching of the textbook Statistics for Geography and Environmental Science by Harris & Jarvis (2011). For further information see www.social-statistics.org
How do Scholars Evaluate and Promote Research Outputs? An NTU Case Study
Authors: Han Zheng, Mojisola Erdt, Yin-Leng Theng
Workshop Website: http://www.altmetrics.ntuchess.com/AROSIM2018/
Statistics for Geography and Environmental Science:an introductory lecture c...Rich Harris
A sample of the instructor's resources to support the textbook Statistics for Geography and Environmental Science. Further information at www.social-statistics.org
SPSS Presentation. topics include general concepts of statistics, basic concepts of SPSS, Variables, types of variables, data and its types, sources of data,four windows of SPSS, viewer window, output viewer. results etc..............................
Here are some of the most important tips for installing laminate flooring. (For more details, check out our three-part article series at http://blog.zenithindustries.net/tips-for-installing-laminate-flooring-part-1.)
If you want to enroll please copy and paste this link:
https://fgxpress.info/Tsukilight/Enrollment/Index?SessionID=459bbff6-4aa8-43fa-9039-192c1143a675#/
If you want more information please email:
admin@puntogaijin.com
In this study, the effect of combining variables from the different data sources for student academic performance prediction was examined using three state-of-the–art classifiers: Decision Tree (DT), Artificial Neural Network (ANN) and Support Vector Machine (SVM). The study examined the use of heterogeneous multi-model ensemble techniques to predict student academic performance based on the combination of these classifiers and three different data sources. A quantitative approach was used to develop the various base classifier models while the ensemble models were developed using stacked generalisation ensemble method in order to overcome the individual weaknesses of the different models. Variables were extracted from the institution’s Student Record System and Learning Management System (Moodle) and from a structured student questionnaire. At present, negligible work has been done using this integrated approach and ensemble techniques especially with aggregated learner data in performance prediction in HE. The empirical results obtained show that the ensemble models.........................
1. Xiaoqing Zhu
3150 Beaujardin Dr.Apt 131B 517-881-7697
Lansing, MI 48910,USA zhuxiaoq@msu.edu
Education
Michigan State University Michigan, USA
Ph.D. Candidate in Statistics Aug. 2011 - May 2015(Expect)
{ Advisor: Dr. Hira L. Koul
{ Candidacy Exam: Statistics, Probability
{ Areas of Study: goodness-of-
2. t testing, time series, nonparametric regression, measurement
error model
Tsinghua University Beijing, China
B.S Mathematics and Physics Aug. 2007 - July 2011
{ Thesis Topic: Molecular mechanisms of drug action
Skills
Technology: R, Matlab, LATEX, SAS, Linux/Unix, StatTools, C/C++, SPSS, ParaView, Python,
SQL
Statistical Analysis: Statistical Modelling, Data Analysis, Quantitative Analysis, Time Series
Analysis, Bias Correction, Clustering
Research and Work Experience
Measurement Error Model Stat. Prob., MSU
Research Assistant under Dr. Hira Koul Aug. 2014-Present
{ Studied the goodness-of-
3. t testing problems in measurement error models
MSU Statistics Student Seminar Stat. Prob., MSU
Chairperson Jan. 2014-Present
{ Organized the seminar, chose topics and invited presenters
{ Topic on Spring 2014: Random Matrix theory
{ Topic on Fall 214: Students research presentations
Weather and Climate Project Geography, MSU
Research Assistant under Dr. Shiyan (Sharon) Zhong Jan. 2012-May 2013
{ Classi
4. ed the dierences between Real Time Mesoscale Analysis (RTMA) and observed
meteorological conditions at Remote Automatic Weather Stations (RAWS) in the northeast
United States
{ Provided visualizations and analysis for seasonal, monthly and hourly data based on times
series, instruments and spatial information, etc for RTMA and RAWS climate data, which is
the mainly statistical analysis in the project
5. nal report and the website
{ Reported the bias corrections methods on the climate data analysis
6. { Prepared fuel and elevation data using Linux scripts
2012 IMSM Workshop for Graduates SAMSI, North Carolina State University
Participant June 2012
{ Made classi
9. nal report, and presented in the end of
workshop.
Bioinformatics Project(Undergraduate Thesis): Automation, THU
Research Assistant under Dr. Shao Li Oct. 2010-July 2011
{ Modeled the relationship between genes of human diseases and syndromes
Beijing Shiji Liangyou Technology Co. Beijing, P.R.China
Market Researcher July 2010- Sept. 2010
{ Investigated the need of the consumers, reported and analyzed on SNS Business using
statistical methods
Department Survey Group: Mathematics, THU
Leader Aug.2008-June 2009
{ Led a group to make surveys, collect, analyze data and
11. nal report
Computer Algebra System Project: Mathematics, THU
Participant March 2010-May 2011
{ Designed advanced algorithms for the computer algebra system
Teaching Experience
Instructor June 2014-July 2014
{ Taught the Introduction to Statistics (STT 200) independently, provided homework, quizzes
and exams.
Teaching Assistant Jan. 2014-May 2014
{ Taught four session recitations of STT 200 and provide quizzes
Grading Sept.2007-Dec. 2014
STT 814: Advanced Stat. for Biologists STT 825: Sample Surveys
STT 351: Prob. and Stat. Engineering STT 315: Intro. Prob. Stat for Business
STT 464: Stat. for Biologists Graduate course: Fractal Geometry(THU)
{ Graded homework, provided example code for homework and helped students via e-mail, oce
hours
{ Tutored in MSU statistics help room
Publications
Goodness-of-t Testing of Error Distribution in Nonparametric ARCH(1) Models (submitted to
Journal of Multivariate Analysis)
Goodness-of-Fit Testing in Measurement Error Models (In progress)
12. An investigation of the dierences between Real Time Mesoscale Analysis and observed
meteorological conditions at RAWS stations in the northeast United States, with Joseph J.
Charney, Shiyuan Zhong, Michael T. Kiefer, Greg Soter, and Adam Cinderich JFSP Research
Project Reports, 2013
Inspection of Composite Assemblies Using a Nondestructive Approach, with Z. Kenz, F. Camacho,
R. Song, Y. Wei, H. Halilovic, H. T. Banks, and S. Hu. Industrial Mathematical and Statistical
Modeling Workshop; Eighteenth Mathematical and Statistical Modeling Workshop for Graduate
Students, CRSC Technical Report TR12-16, (July 2012) 76-119.
Talks and Presentations
Oct. 2014. Introduction to Khmaladze Martingale Transformation. MSU student seminar
Aug. 2014. Goodness-of-Fit Testing in Nonparametric Autoregressive Conditional Heteroscedastic
Models. Boston 2014 Joint Statistical Meetings(JSM)
Apr. 2014. Random Matrices with Independent Rows or Columns. MSU student seminar
Nov. 2013 A sequential importance sampling algorithm for generating random graphs with
prescribed degrees. MSU student seminar
Feb. 2013 Generalized Hyper Markov Laws for DAG. MSU student seminar
AWARDS HONOURS
Finalist of the Big Data World Championships - TEXATA (top12 over 2000+ competitors) . 2014
College of Natural Science Summer Dissertation Continuation Fellowship($6000) . . . . . . . 2014
Chinese Undergraduate Mathematical Contest in Modeling (2rd Prize) . . . . . . . . . . . . 2011
Tsinghua University Excellent student Leadership . . . . . . . . . . . . . . . . . . . . . . . . 2011
Tsinghua University Undergraduate Mathematical Contest in Modeling (5th out of 60) . . . 2010
Outstanding Communist Youth League member . . . . . . . . . . . . . . . . . . . . . . . . . 2010
Leadership Experience (selected)
Department Women Soccer Team Mathematics, THU
Captain 2010-2011
Class JS73 and JK78 Mathematics, THU
Monitor 2010-2011
Centennial Celebration of THU THU
Major Volunteer 2010-2011