Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Learn essential statistical methods and data analysis techniques for addressing questions in social sciences, economics, and policy research through this comprehensive MIT course. Master fundamental concepts in probability and statistics before progressing to advanced topics including regression analysis, econometrics, experimental design, randomized controlled trials, A/B testing, machine learning, and data visualization. Explore real-world applications through frontier research examples while developing practical skills in the R statistical programming language. Cover key topics from basic probability theory and random variables to complex issues like omitted variable bias, endogeneity, and instrumental variables. Gain hands-on experience with data collection, summarization, hypothesis testing, confidence intervals, and causal inference methods. Practice creating effective data visualizations and conducting self-directed empirical analyses. Understand how to design and analyze randomized experiments, perform nonparametric comparisons, and handle practical challenges in regression modeling. Build a solid foundation in statistical thinking that bridges theoretical concepts with practical applications in social science research.
