Data Analysis with Python

QMSS S 5019 Data Analysis with Python

MW 10:10am-12:00pm

Join this summer course from ISERP and the Columbia School of Professional Studies (SPS).

The course will run for the 6-week duration of the Columbia Summer Session D, from May 28th through July 5th, 2019.

QMSS S5019 Data Analysis with Python is open to the public but requires registration with SPS prior to course registration. For more information on SPS application and registration, please visit their website and explore your options here

Course Goals:

QMSS S5019 Data Analysis with Python is meant to provide an introduction to regression and applied statistics for the social sciences, with a strong emphasis on utilizing the Python software language to perform the key tasks in the data analysis workflow. The chief goal is to help students generate and interpret quantitative data in helpful and provocative ways. The hope is that by trying to measure the social world, students will see their thinking become clearer and their understandings of concepts grow more complex. They will also become competent at reading statistical results in social science publications and in other media. Only basic mathematics skills are assumed, but some more advanced math will be introduced as needed. For this course, a critical goal is to teach students how to manipulate and analyze data themselves using statistical software. We will focus almost exclusively on Python for this class (although, there will be a few cases where we will run R through Python because R can more readily do things than Python). There will be Python write-up assignments nearly every week, tied to hands-on data analysis lab sessions. These weekly assignments will be devoted to using Python to practice commands and to develop a paper using the General Social Survey, World Values Survey or another dataset of the student’s choosing. Credits: 3 points

 

Instructor: Gregory M. Eirich

Gregory M. Eirich is the Director of the Quantitative Methods in the Social Sciences (QMSS) MA program at Columbia and teaches many courses for the program on various quantitative methodologies.

 

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