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. 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 assessment course should only be taken by learners who have completed and passed 14.310x - Data Analysis for Social Scientists and intend to pursue the MicroMasters credential in Statistics and Data Science. To get credit in this MicroMasters program:
- Enroll in both this assessment course and the content course 14.310x - Data Analysis for Social Scientists (Note: There is no additional fee to enroll in the content course),
- Complete the content course 14.310x with a passing grade,
- Come back to this course and take the exam to earn your verified certificate that will count toward the MicroMasters credential in Statistics and Data Science.
This assessment course, along with the content course 14.310x - Data Analysis for Social Scientists, is part of the MITx MicroMasters Program in Statistics and Data Science. Master the skills needed to be an informed and effective practitioner of data science. You will complete this course and three others from MITx, at a similar pace and level of rigor as an on-campus course at MIT, and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities. To learn more about this program, please visit https://micromasters.mit.edu/ds/.