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MITx: Statistics and Data Science MicroMasters

Data Analysis for Social Scientists

Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest.

Syllabus

  • Module One: Introduction
  • Module Two: Fundamentals of Probability, Random Variables, Joint Distributions and Collecting Data
  • Module Three: Describing Data, Joint and Conditional Distributions of Random Variables
  • Module Four: Functions and Moments of a Random Variables & Intro to Regressions
  • Module Five: Special Distributions, the Sample Mean, the Central Limit Theorem
  • Module Six: Assessing and Deriving Estimators - Confidence Intervals, and Hypothesis Testing
  • Module Seven: Causality, Analyzing Randomized Experiments, & Nonparametric Regression
  • Module Eight: Single and Multivariate Linear Models
  • Module Nine: Practical Issues in Running Regressions, and Omitted Variable Bias
  • Module Ten: Endogeneity, Instrumental Variables, and Experimental Design
  • Module Eleven: Intro to Machine Learning and Data Visualization Optional: Writing an Empirical Paper

The Codes were tested on Google Colab Plataform.

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Repository of MITx 14.310Fx course exercicies: Data Analysis for Social Scientists.

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