Combining and Analyzing Complex Data
FREE
In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries. The University of Maryland is the state’s flagship university and one of the nation’s preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of the national academies and scores of Fulbright scholars. The institution has a $1.8 billion operating budget, secures $500 million annually in external research funding and recently completed a $1 billion fundraising campaign.
Instructor Details
Courses : 1
Specification: Combining and Analyzing Complex Data
|
4 reviews for Combining and Analyzing Complex Data
Add a review Cancel reply
This site uses Akismet to reduce spam. Learn how your comment data is processed.
Price | Free |
---|---|
Provider | |
Duration | 7 hours |
Year | 2017 |
Language | English |
Certificate | Yes |
Quizzes | Yes |
FREE
Jorge F d l V G –
I found very difficult to understand the way professsor Valliant explains concepts. Also I think that the quizzes are not necesarily correlated with the presentation or talks. This is challenging, and usually is good, but there are no enough guides or Reading material to conpensate the lack of clarity and the extra concepts needed to know. What saves this course was the participation of Profess
Jose A R N –
My name is Jose Antonio. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11) I did this course to get new knowledge about Big Data and better understand the technology and your practical applications. The course was excellent and the classes well taught by teachers. Congratulations to Coursera team and Instructors. Regards. Jose Antonio.
Thomas A K –
Easy to understand
Adam P –
I liked the practical examples