In this course, you will obtain some insights about marketing to help determine whether there is an opportunity that actually exists in the marketplace and whether it is valuable and actionable for your organization or client. Week 1: Assess methods available for creating quantitative surveys, along with their advantages and disadvantages. Identify the type of questions that should be asked and avoid unambiguous survey questions. Week 2: Design, test, and implement a survey by identifying the target audience and maximizing response rates. You will have an opportunity to use Qualtrics, a survey software tool, to launch your own survey. Week 3: Analyze statistical models that can be applied to your marketing data, so that you can make data-driven decisions about your marketing mix. Week 4: Predict most likely outcomes from the marketing decisions and match the type of analysis needed for your business problem. Take Quantitative Research as a standalone course or as part of the Market Research Specialization. You should have equivalent experience to completing the second course in this specialization, Qualitative Research, before taking this course. By completing the third class in the Specialization, you will gain the skills needed to succeed in the full program.
I enjoyed every bit of the course content most especially the analytical aspect of it. I have indeed acquired an invaluable skill. Thanks to our amazing instructors.
This course helped me understand the relavant knowledge to undertake Quantitative Research.Thanks a lot to the Instructors.John Paco
This course is one of the best courses each researcher needs to take. I strongly recommend this course because of its rich material and nice teaching of the instructors.
A good insight from this course. Hope this will help us to boost our career. Thanks for the lessons.
the course will give you the Theoritcal as well as practical knowledge of Quantitative Research
An amazing course. You should have atleast a degree in statitics to understand the subject.
Very Useful course. Instructors and their Pedagogy and Learning strategies are amazing
Qualitative portion is very helpful. The quantitative part is hit or miss, a lot of it is very hypothetical and not useful when actually implementing the approach in Excel.
very helpful in building foundations for market analysis
It helped me get through market research now i feel comfortable doing some analysis and market research questionnaire building etcI will recommend this course to my peers
Its a platform to enhance your skills and learn the things efficiently with a practical approachThanks to Coursera Team
A perfect blend of information and knowledge needed by newcomers to this field
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The second part of the course was rushed and I could not fully comprehend what the lecturer was saying. Now I am stuck with an assignment that I am struggling to understand and finish.
Very strange and convoluted course. Not sure if it was just me, but I felt I was hit with a lot of math and information I was not prepped for from the previous courses or even the previous weeks. This is definitely the weak link in the entire research marketing specialization.
Also I feel the speaker speaks way too fast and many of the course files seemed to be missing information.
The last two modules on Statistics were explained too generally and they are difficult to follow. The modules intend to cover Statistics in some detail but it becomes fuzzy and heavy. There are many "practice quizzes" which I did not find helpful at all, I had to look online for information to answer them, however they are compulsory (70% pass grade). It might be better to leave Statistics separately, on a different course altogether.
Unfortunately, the level of teaching of Prof. Dr. Olivier Rubel did not match what the course had promised. The level of detail explanations wasn't high enough, many things were merely mentioned without describing the meaning of statistic calculations, the speach was very hard to follow due to a hardly understandable accent in English and the lecture notes didn't always make sense. I would not suggest Prof. Rubel should teach this course.
Concepts could have been thought a little more clearly. I felt like some of the key concepts were rushed.
The second half of the course was a convoluted statistics lesson that had little to do with what we were learning earlier in the specialization. The instructor was unable to deliver the intended training. The assignment was almost impossible to complete without help from other online sources and lectures. Some of the course links within the course are outdated and don't work.
We went from a Quant Research intro into an advanced stats space which likely requires an existing background in stats. This could have been an entire course on its own (if not more) For example, we were asked to run regression in the course assignment, but there wasn't enough info in the videos and course materials to actually follow all the steps on excel. Additionally, the course clearly missed important aspects of Quant Research. There was no mention of weighting, sample balancing, and no training on how to run cross tabs in softwares such as SPSS. I believe that is something that more researchers do vs. running complex statistics and regression.
I would not recommend this course and if it wasn't for the specialization (or the fact that I was halfway through the specialization), I would not have opted out of this course.
The instructor's french accent gives non-native english speakers a very hard time to understand the content. It's an unnecessary frustration that puts us at 0.5x speed due to his odd pronunciation. I would categorize it as midly-to-moderately infurating. The course covers good basic content, but does not prepare the student to learn how to put it in practice at all, making the graded activities somewhat of a nightmare to finish. I had to work many extra hours seeking external sources because the course is simply not enough, unlike it's Qual Research counterpart. All in all, good premise, good plan, mediocre execution. 3 stars.
Its a platform to enhance your skills and learn the things efficiently with a practical approach
Thanks to Coursera Team
SUPER
I thought this course was good, and helped balance what was learned in the earlier courses. What keeps this from being five stars is that the second half of this course is well taught, but the instructions on what to focus on to be successful with the quizzes and assignements were not accurate at times.
The course requires knowledge of statistics and without it it is rather difficult to follow. However, it provides a decent overview of what quantitative research is and how it is conducted. Not recommended for beginners without prior knowledge in statistics.
Course based on bite-sized lessons, which is perfect for online courses. Lessons have good examples, and clearly explain formulae. However, there are several issues with this course: 1. I miss an overall guide / structure to follow through the different lessons and why we are studying them. 2. A final cheat sheet would be great to review and go back to key insights quickly. 3. Some values are incorrect (such as when calculating confidence intervals). 4. I miss a more clear explanation of when to use which method (e.g., using z score vs using 5. The final assignment shows you can translate ordinal scales into intervals but can't remember this being mentioned through the lessons. 6. The exercises for modules 3 & 4 are much harder than for module 1 & 2 (expected?). Overall: Good insights, good intentions, but lacking the rigour to apply them to real-world projects.
The course is a great introduction to quantitative research. I always wanted to learn how to write effective surveys, and this course definitely helped in teaching the basics. However, I was left completely lost in the second half of the course. I just feel that the lecture structure was quite a mess and I found myself Googling a lot of the stuff taught just to complete assignments. I took statistics during graduate school so I knew some of the basic things. However, at this time, I think I need to take another statistics course just so that I can learn more about analyzing the data I collect.
Coursera needs to have a team of teaching assistants. When I needed help there was none to be found. In discussion forum all one sees are "please review my work" type posts. I probably could have done better if I had access to help. But I am grateful to have passed!
A good beginners course, however not enough for someone who might need the knowledge to work/start a new career. The knowledge was kind of out dated since modern technology evolved so much since then. Hope this could be refreshed with some new info someday!
The second part of the course needs a lot more explanation.
The first two modules were great and at the same pace as the ones before. However, the last two were extremely rushed. The instructor failed to accurately walk through everything that would eventually be tested on. With these sections heavily focusing on statistics, it would be helpful to know how certain numbers/solutions came to be. It would be helpful to give more example of how the formulas are used with all pieces plugged in rather than just showing us a complex formula and then testing us on it. Lastly, someone should go in and spell/grammar check the slides.
Unfortunately the statics part of the course is just terrible, impossible to follow. Exercises are not clear with question about the topics not even mentioned in the lecture. I used You tube all the time to be able to understand anything.
Instructors are not that good at explaining concepts
The course rarely touches on the quantitative analysis part of the course
very bad espcailly for the statical stuff , just theory without any digging in the information