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    Shengzhi Wang

    Shengzhi Wang

    Ph.D. student at The Chinese University of Hong Kong

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    Teaching Materials

    Poli 891: Lab for Advanced Political Data Science

    • Programming Style
    • Functional Programming in R
    • Multilevel Linear Models
      • Individual Exercise Solution
    • Multilevel Generalized Linear Models
      • Individual Exercise Solution
    • Multilevel Models for Correlated Data
    • Multilevel Regression with Poststratification
      • Individual Exercise Solution
    • High Performance Computing
    • Working with Strings
      • Individual Exercise Solution
    • Structural Topic Models
      • Individual Exercise Solution
    • Item Response Theory Models
      • Individual Exercise Solution
    • Performance, Optimization, and Parallelization
    • Regression and Classification Trees
      • Individual Exercise Solution
    • Elastic Net, LASSO, and Ridge Regression
      • Individual Exercise Solution
    • Latent Space Networks

    Poli 281: Quantitative Research in Political Science

    • Introduction to R
    • Working with Data in R
    • Writing R Scripts
    • Visualizing Discrete and Continuous Data

    Poli 891: Machine Learning

    • Artificial Neural Networks

    PS 3090: The Scientific Study of Civil Wars

    • Regression in 10 Minutes
    • What’s in a War?

    PS 3171: International Conflict Management and Resolution

    • Measuring the Democratic Peace

    ICPSR: Introduction to Applied Bayesian Modeling

    • Using Stan to Estimate Bayesian Models

    Peace Science 2018: Measurement Workshop

    • Item Response Theory Models
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