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Opiniones y comentarios de aprendices correspondientes a Dealing With Missing Data por parte de Universidad de Maryland en College Park

88 calificaciones
22 revisiones

Acerca del Curso

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®....

Principales revisiones


Aug 20, 2019

interesting material, well taught, lots of short quizzes to enforce understanding.


Jun 05, 2017

This course quite help to get as much reliable data as possible for any survey.

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1 - 19 de 19 revisiones para Dealing With Missing Data

por Martyns N

May 17, 2019

The professor was not very explanatory and I just managed to finish the course out of my sheer strong will

por Ahmed I

Sep 01, 2016

The quality of the presentation is very low, and way below the quality in other courses. The assignments are very poorly designed. This is not a subjective personal experience. This is based on discussions with other learners in the forum who have expressed disappointment and frustration.

por marine h

Feb 13, 2019

very idfficult to understand. The sound of the videio is so low that most of it is impossible to understand, I had to try 10 times some of the tests because couldn't find the answer and had to guess it!

por Mohammad M

Jun 05, 2017

This course quite help to get as much reliable data as possible for any survey.

por Reni A

Apr 05, 2018

Prof. Richard Valliant, Ph.D. clearly enough explain all of these course materials. I will use these materials to dealing missing data on our census or survey. I believe that these materials were very helpful for me and my agency.

Thank you very much for all of this course.

por Neeraj K

Oct 26, 2016

it is very informative

por Carlos F P

Apr 27, 2017

Excellent review of relevant material.

por Tin K O

Jan 25, 2017

Good knowledge about Non-responses!

por Anna B R

Jan 24, 2018

Great course!

por Zachary M

Aug 20, 2019

interesting material, well taught, lots of short quizzes to enforce understanding.

por Hussein E

Dec 25, 2017

This is a higher level course. Good for beginners.

por Zachary H

Aug 31, 2016

I was interested in the topic. The course itself seems like just a starting point with understanding dealing with missing data. I wanted to know more and see more examples than the videos offered. I also would have appreciated including examples from more than just R, though I did appreciate the minimal discussion of other statistical software that are available for statistical analysis when it did occur.

por Iyshia L

Nov 08, 2018

As others have stated before the audio is REALLY LOW. It makes it very difficult to hear him without headphones for my phone. The course was fine, overall.

por Lingbing F

Feb 10, 2019

The topic of this course is attractive as it is hard to get from elsewhere. However, the content of this course is actually quite barren, practices are easy and not closely refective of the corresponding videos.

The fourth week is most interesting and I was happy to know that multiple imputation is actually not key on the "imputation" part. It emphasizes the fact that missingness should be considered as uncertainty in modelling.

After all, this is a interesting course and can be better designed and delievered. Thanks to the team.

por Anandita G

Nov 03, 2018

There is scope for a lot of improvement in terms of quality of content as well as videos. There also appeared to be technical issues in the quizzes wherein the correct responses were often returned as incorrect & vice-versa, for a few quizzes. Without a moderator, queries are not addressed and nobody appears to be keeping track of the feedback. I was disappointed in the course since the previous courses in the specialization were far better designed and executed.

por Evan

Dec 24, 2016

While this course seems to have potential, there are many aspects of it that don't result in a great learning experience. The course resources comprise of videos and notes. The videos are informative but the notes are fairly lacking. Perhaps the biggest issue that I found with this course was the disconnect between the material covered in the videos and that which was tested on the quizzes. Often times the quiz questions were either painfully easy or worded in such a way that was not verifiable in any of the class resources. As a result, confusion occurred sometimes more often than true learning. A topic such as missing data is naturally very complex and I wouldn't expect a short course on Coursera to be able to adequately cover it. However, I do think that a lot more could be done to improve the value of this course even if that means changing the scope of the materials. Also, the lack of responsiveness to issues raised on the forum and issue-reporting buttons was a disappointment.

por Réjane F R

Dec 22, 2016

The contents of this course could be interesting, but they end up being terribly boring. The course lacks examples to bring things to life. A pity!

por Margie H

Aug 30, 2016

I wrote some indepth feedback, but par for the course, I can't save it - either here or on the discussion board. Nothing obscene, but certainly some major frustration with format, inconsistencies in scoring and format, information not reviewed in the course on some of the quizzes, the fact that Coursera keeps trying to sell me the specialty, the lack of ANY moderator on the discussion board to provide assistance...and can go on with the technical issues to but I won't!

por Hiroki N

Nov 17, 2017

the course materials are of very low quality.