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學生對 马里兰大学帕克分校 提供的 Combining and Analyzing Complex Data 的評價和反饋

54 個評分
8 條評論


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....



1 - Combining and Analyzing Complex Data 的 8 個評論(共 8 個)

創建者 José A R N


My name is Jose Antonio. I am looking for a new Data Scientist career (

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.


Jose Antonio.

創建者 Roberto D C B



The course was useful and informative to me.

Teachers made complex topics clear and understandable.

創建者 Adam P


I liked the practical examples

創建者 Jorge 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

創建者 Daniele C


The good part of the course is the one dealt with by Frauke Kreuter.

創建者 Ana A


Great course! Thanks, Professsor Valliant and Professor Frauke Kreuter.

創建者 Enrique A M


Mil gracias maestro Richard, Mil gracias Coursera.

創建者 Thomas A K


Easy to understand