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Workshops on Foundational and Cutting-Edge Methods of Statistical Analysis
2023-06-29  点击:[]

Workshops on Foundational and Cutting-Edge Methods of

Statistical Analysis

June 12thto June 20th, 2023

Xi’an, China

 

[Introduction]

Big Data, Machine Learning, Social Computing, and Artificial Intelligence are currently the cutting-edge methods and applications to address research questions of social behavioral, health, and policy research. Through an introduction to the basics of statistical methods and cutting-edge topics, students will be able to understand the transformation that quantitative research methods are undergoing during the information revolution. This workshop is going to discuss how to integrate the changes brought about by the computer technology revolution with the existing results of traditional methodological science, enhance students’ interest in statistical learning and big data research, and help acquire ideas and orientation for further study of more advanced methodological science.

[Course Leader]

 

Shenyang Guo

 

Shenyang Guo is the Frank J. Bruno Distinguished Professor of Social Work Research at Washington University in St. Louis, USA, and Guest Professor at Xi’an Jiaotong University. He is a fellow of the American Academy of Social Work and Social Welfare and Vice President of the Society of Social Work Research for 2021. He has expertise in applying advanced statistical models to solving social welfare problems and has taught graduate courses that address event history analysis, hierarchical linear modeling, growth curve modeling, propensity score analysis, and program evaluation. He has published over 100 peer-reviewed papers in the field of social evidence-based research and social work.He is one of the top 2% of scientists in the world in 2021, as selected by researchers at PLOS Biology and Stanford University, and one of the top 100 contributors to social work in the world, ranked 37th by Sage magazine in 2022.

[Curriculum System]

Based on general knowledge of statistical methods, the workshops discuss the algebra of expectations, likelihood functions, generalized boosted regression, general structural equation models, unobserved heterogeneity, and causality. The workshops introduce interesting topics about the opportunities and challenges of statistical models. It will also review the social impact and theoretical iteration of statistical methods, explore the content of Big Data, Machine Learning, Social Computing, and Artificial Intelligence, and provide new insights for future academic research.

[Curriculum Format]

synchronous online and offline teaching

[Curriculum Arrangement]

 

Part

Date

Content

Hours

1

June 12th

D-206

The algebra of expectations and its applications

18:30-21:30

3h

2

June 13th

D-206

The Maximum Likelihood and its applications

18:30-21:30

3h

3

June 14th

D-206

The Generalized Linear Model and its explanations

18:30-21:30

3h

4

June 16th

C-206

The results of Cox Regression

18:30-21:30

3h

5

June 17th

C-206

The complication and simplification of statistical modeling with the example of structural equation models

18:30-21:30

3h

6

June 18th

C-206

The Propensity Score Subclassification

18:30-21:30

3h

7

June 19th

C-206

The unobserved heterogeneity

18:30-21:30

3h

8

June 20th

C-206

The argument and challenge of causal inference

18:30-21:30

3h

 

[Recorded Courses Information]

At present, the onlyonline live broadcasting websiteis available after registration.

 

[Enrollment Target]

Graduate students with unlimited grades as well as undergraduates. An unlimited number of students offline and online.Undergraduate and international studentsare expected to register.

[Application]

Students who are interested in applying to attend this workshop can scan the OR code link below.

 


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