HE
This is a higher level course. Good for beginners.
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®.
HE
This is a higher level course. Good for beginners.
MM
This course quite help to get as much reliable data as possible for any survey.
ZM
interesting material, well taught, lots of short quizzes to enforce understanding.
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The professor was not very explanatory and I just managed to finish the course out of my sheer strong will
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!
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.
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.
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.
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.
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.
I agree with the other reviewers. This course was terrible. Unlike other professors who have taught courses in the survey specialization, Professor Valliant made no attempt to explain the concepts in a way that would be comprehensible to an educated layperson. Instead, the lectures were rushed and laden with unexplained jargon. In order to have a minimal grasp of what is being presented, you must have a foundational knowledge of intermediate statistics and basic econometrics. Anything less than that and you'll be in over your head.
Compared to the other courses in the specialization, this course is not good. The professor mostly recites what he knows, but he is not trying his best to explain new concepts to students. Explanations should be more thorough, finding different ways to explain things, not just putting a slide and repeating. Examples are too far away from concepts, so the concept is explained without an example and later the example is givien. This makes it harder to understand the concept.
interesting material, well taught, lots of short quizzes to enforce understanding.
This course quite help to get as much reliable data as possible for any survey.
Excellent review of relevant material.
Good knowledge about Non-responses!
Very useful and informative!
it is very informative
Great course!
The course material was good but there were a couple of questions on the exams that weren't covered until the next module. Otherwise everything was very easy to follow and understand. I liked that the videos were shorter in duration as I was able to stay focused easier that way given the material can be a bit on the dry side with all the formulas, etc.
I found it hard to follow this course and didn't find the instructor very engaging for some reason. More assignments rather than just quizzes would have helped. But the information covered is good and something I will refer back to when I need to.
The materials do not helful for anwering the quizes. Some quize's questions for the next chapter are asked in the previous chapter.
the format can be delivered better. the faculty is basically using PPT recording and reading off the slides. As for the assessment, the R software should be used as an assessment to deepen the learning from the course. Design of module should be relooked