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Combining and Analyzing Complex Data, University of Maryland, College Park

4.2
29 calificaciones
4 revisiones

Acerca de este Curso

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....
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4 revisiones

por Adam Preston

Mar 07, 2018

I liked the practical examples

por Thomas A. Kanu

Sep 04, 2017

Easy to understand

por Jose Antonio Ribeiro Neto

Jul 09, 2017

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.

por Jorge Francisco de la Vega Gongora

Jun 13, 2017

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