EdX

Data Analysis in Social Science—Assessing Your Knowledge (edX)

Offered by MIT, MITx,
Data Analysis in Social Science—Assessing Your Knowledge (edX)

Learn the methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest, and then assess that knowledge-- Part of the MITx MicroMasters program in Statistics and Data Science. This course consists of an assessment that tests your knowledge on the course content from 14.310x - Data Analysis for Social Scientists, a statistics and data analysis course that will introduce you to the essential notions of probability and statistics.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

It will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. It will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, it will provide instruction for how to use the statistical package R and opportunities for students to perform self-directed empirical analyses.
This course is part of the Statistics and Data Science MicroMasters program.

What you'll learn
You will be tested on your knowledge in the following areas:

  • Intuition behind probability and statistical analysis
  • How to summarize and describe data
  • A basic understanding of various methods of evaluating social programs
  • How to present results in a compelling and truthful way
  • Skills and tools for using R for data analysis

Prerequisites
IMPORTANT: You must first complete 14.310x - Data Analysis for Social Scientists with a passing grade in order to take this assessment.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Analytics for Decision Making (edX) EdX
Babson College

Analytics for Decision Making (edX)

Discover the foundational concepts that support modern data science and learn to analyze various data types and quality to make smart business decisions. Want to know how to avoid bad decisions with data? Making good decisions with data can give you a distinct competitive advantage in business. This statistics and data analysis course will help you understand the fundamental concepts of sound statistical thinking that can be applied in surprisingly wide contexts, sometimes even before there is any data! Key concepts like understanding variation, perceiving relative risk of alternative decisions, and pinpointing sources of variation will be highlighted.

Self Paced
Self-Paced
Analyzing and Visualizing Data with Power BI (edX) EdX
Davidson College,DavidsonX

Analyzing and Visualizing Data with Power BI (edX)

Step up your analytics game and learn one of the most in-demand job skills in the United States. Power BI is a robust business analytics and visualization tool from Microsoft that helps data professionals bring their data to life and tell more meaningful stores. This four-week course is a beginner's guide to working with data in Power BI and is perfect for professionals. You'll become confident in working with data, creating data visualizations, and preparing reports and dashboards.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced
Datos para la efectividad de las políticas públicas (edX) EdX
Inter-American Development Bank - IDB,IDBx

Datos para la efectividad de las políticas públicas (edX)

Este curso te ayudará a tomar el control de los datos y familiarizarte con las herramientas para utilizarlos en la planificación, gestión y evaluación de políticas publicas. En esta era de la información, los datos están disponibles en todos lados y crecen a una tasa exponencial. ¿Cómo podemos darles sentido a todos los datos y aprovecharlos en el momento de tomar decisiones?, ¿cómo los utilizamos para que nos ayuden a guiar la gestión y planificación de nuestras políticas? Tanto si eres ciudadano como planificador de políticas, deberías poder responder a estas preguntas.

Self Paced
Self-Paced
Python for Data Science (edX) EdX
University of California, San Diego,UC San DiegoX

Python for Data Science (edX)

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets. In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?

Self Paced
Self-Paced
Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Self Paced
Self-Paced
Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Learn to use R programming to apply linear models to analyze data in life sciences. Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language.

Self Paced
Self-Paced
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

Self Paced
Self-Paced
R Data Science Capstone Project (edX) EdX
IBM

R Data Science Capstone Project (edX)

Apply various data analysis and visualization skills and techniques you have learned by taking on the role of a data scientist working with real-world data sets. In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R or IBM Data Analytics with Excel and R Professional Certificate Programs.

Self Paced
Self-Paced
High-Dimensional Data Analysis (edX) EdX
HarvardX,Harvard University

High-Dimensional Data Analysis (edX)

A focus on several techniques that are widely used in the analysis of high-dimensional data. If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis.

Self Paced
Self-Paced
Observation Theory: Estimating the Unknown (edX) EdX
Delft University of Technology,DelftX

Observation Theory: Estimating the Unknown (edX)

Learn how to estimate parameters from observational data for real-world engineering applications and assess the quality of the results. Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.

Self Paced
Self-Paced
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX)

This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug”?

Self Paced
Self-Paced