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Data Analysis & Statistics

Resources on the topics covered in introductory statistics and data analysis classes (e.g., PUBP 511, COMM 650)

Path Analysis & Structural Equation Modeling (SEM)

Structural Equation Modeling

Factor Analysis

Time Series & Panel Data Analysis

Time Series & Panel Data

If you are going to do data analysis involving time, there are several issues you need to account for:

  • Correlation with Time: Two variables are strongly correlated, but it is simply that both trend over time.
    • You can control for the time variable (e.g., year)
    • You can examine the changes from year to year ("Differencing")
  • Monetary Inflation: The value of money is not constant over time, and inflation is not constant either.
  • Time-lagged relationships: One variable may affect the other only after a period of time.
Forecasting

Machine Learning

Machine Learning

Machine learning is a branch of artificial intelligence focusing on the training of statistical models and algorithms that can automatically improve their performance by discovering and retaining patterns these models observe in data (i.e., "learning"). In practice, this means being very accurate at prediction.

This focus on prediction differentiates machine learning from traditional statistical inference in important ways. Machine learning also uses different words than traditional statistics to describe the same thing (e.g., "features" instead of "variables")