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  1. Beginner: Using R and Data in Applied Econometrics
  2. Dispersion and Dependence
  • Learn by Skill Level


  • Getting Started: Introduction to Data, R, and Econometrics
    • Intro to JupyterNotebooks
    • Intro to R
    • Intro to Data (Part 1)
    • Intro to Data (Part 2)

  • Beginner: Using R and Data in Applied Econometrics
    • Introduction to Statistics I
    • Introduction to Statistics II
    • Central Tendency
    • Dispersion and Dependence
    • Confidence Intervals
    • Hypothesis Testing
    • Data Visualization I
    • Data Visualization II
    • Distributions
    • Sampling Distributions
    • Simple Regression

  • Intermediate: Econometrics and Modeling Using R
    • Simple Regression
    • Multiple Regression
    • Issues in Regression
    • Interactions

    • Geographic Computation
    • Chi-Square Test
    • t-test
    • ANOVA
    • Regression
    • Wrangling and Visualizing Data

  • Advanced Modules
    • Classification and Clustering
    • Differences In Differences
    • Geospatial I
    • Geospatial II
    • Instrumental Variables I
    • Instrumental Variables II
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    • Linear Differencing
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    • Sentiment Analysis Using LLMs (Python)
    • Transcription (Python)
    • Vocalization (Python)
    • Word Embeddings (Python)
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    • Panel Data
    • Synthetic Controls

1.2 - Beginner - Dispersion and Dependence

econ 325
central tendency
descriptive statistics
variance
covariance
standard deviation
correlation
beginner
R
interquartile range
beginner
In this notebook we explore how data is spread out, and what that means for its interpretation. This includes both how individual values may vary, and how values may co-vary with one another.
Published

12 January 2023

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Central Tendency
Confidence Intervals
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