Name: MIT OCW 14.310x Data Analysis for Social Scientists (Spring 2023)
Creator: Prof. Esther Duflo and Dr. Sara Ellison
License: https://academictorrents.com/nolicensespecified

MIT OCW 14.310x Data Analysis for Social Scientists (Spring 2023) (46 files)

Lecture 23： Visualizing Data.mp4	217.77MB
Lecture 23： Visualizing Data.en.vtt	123.34kB
Lecture 22： Experimental Design.mp4	233.18MB
Lecture 22： Experimental Design.en.vtt	105.55kB
Lecture 21： Endogeneity and Instrument Variables.mp4	301.93MB
Lecture 21： Endogeneity and Instrument Variables.en.vtt	105.30kB
Lecture 20： Omitted Variable Bias.mp4	255.05MB
Lecture 20： Omitted Variable Bias.en.vtt	118.43kB
Lecture 19： Practical Issues in Running Regressions.mp4	378.85MB
Lecture 19： Practical Issues in Running Regressions.en.vtt	111.02kB
Lecture 18： The Multivariate Model.mp4	194.52MB
Lecture 18： The Multivariate Model.en.vtt	53.56kB
Lecture 17： The Linear Model.mp4	203.31MB
Lecture 17： The Linear Model.en.vtt	103.36kB
Lecture 16： (More) Explanatory Data Analysis： Nonparametric Comparisons and Regressions.mp4	344.98MB
Lecture 16： (More) Explanatory Data Analysis： Nonparametric Comparisons and Regressions.en.vtt	127.76kB
Lecture 15： Analyzing Randomized Experiments.mp4	256.73MB
Lecture 15： Analyzing Randomized Experiments.en.vtt	110.93kB
Lecture 14： Causality.mp4	142.49MB
Lecture 14： Causality.en.vtt	110.90kB
Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations.mp4	291.46MB
Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations.en.vtt	105.37kB
Lecture 12： Assessing and Deriving Estimators.mp4	211.82MB
Lecture 12： Assessing and Deriving Estimators.en.vtt	86.00kB
Lecture 11： Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation.mp4	283.13MB
Lecture 11： Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation.en.vtt	96.77kB
Lecture 10： Special Distributions.mp4	303.25MB
Lecture 10： Special Distributions.en.vtt	106.48kB
Lecture 09： Expectation, Variance, and Introduction to Regression.mp4	190.11MB
Lecture 09： Expectation, Variance, and Introduction to Regression.en.vtt	87.12kB
Lecture 08： Moments of Distribution.mp4	349.02MB
Lecture 08： Moments of Distribution.en.vtt	104.70kB
Lecture 07： Functions of Random Variables.mp4	379.46MB
Lecture 07： Functions of Random Variables.en.vtt	102.28kB
Lecture 06： Joint, Marginal, and Conditional Distributions.mp4	155.18MB
Lecture 06： Joint, Marginal, and Conditional Distributions.en.vtt	70.84kB
Lecture 05： Summarizing and Describing Data.mp4	222.62MB
Lecture 05： Summarizing and Describing Data.en.vtt	99.77kB
Lecture 04： Gathering and Collecting Data.mp4	352.89MB
Lecture 04： Gathering and Collecting Data.en.vtt	127.48kB
Lecture 03： Random Variables, Distributions, and Joint Distributions.mp4	251.21MB
Lecture 03： Random Variables, Distributions, and Joint Distributions.en.vtt	88.26kB
Lecture 02： Fundamentals of Probability.mp4	236.03MB
Lecture 02： Fundamentals of Probability.en.vtt	88.27kB
Lecture 01： Introduction to 14.310x Data Analysis for Social Scientists.mp4	142.30MB
Lecture 01： Introduction to 14.310x Data Analysis for Social Scientists.en.vtt	88.05kB

Type: Course
Tags: mit ocw

Bibtex:

@article{,
title= {MIT OCW 14.310x Data Analysis for Social Scientists (Spring 2023)},
journal= {},
author= {Prof. Esther Duflo and Dr. Sara Ellison},
year= {2023},
url= {https://ocw.mit.edu/courses/14-310x-data-analysis-for-social-scientists-spring-2023/},
abstract= {This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with essential notions of probability and statistics. We will proceed to cover techniques in modern data analysis: regression and econometrics, design of experiments, randomized control trials (and A/B testing), machine learning, and data visualization.

We will illustrate these concepts with applications drawn from real-world examples and frontier research. Finally, we will provide instruction on the use of the statistical package R, and opportunities for students to perform self-directed empirical analyses.},
keywords= {mit ocw},
terms= {},
license= {CC BY-NC-SA 4.0},
superseded= {}
}

MIT OCW 14.310x Data Analysis for Social Scientists (Spring 2023) Prof. Esther Duflo and Dr. Sara Ellison

MIT OCW 14.310x Data Analysis for Social Scientists (Spring 2023)
Prof. Esther Duflo and Dr. Sara Ellison