1. Teaching speed in the video was a little bit slow and quite boring

2. Hypothesis testing, A/B testing, sampling, and probability distribution are all well covered.

3. Case studies are the most interesting and the best part of the course.

The materials and presentations are excellent, but I am not a fan of the busy work involved in the end of course PACE portfolio work. Professional presentation is certainly important, but you end up diluting the course by including so much of this material. Furthermore, having worked on many projects, I can tell you that the workflow process is so iterative that trying to "shoe horn" the process into a four letter acronym -- which is better than the six letter acronym in the previous specialization -- is both reductionistic and frankly artificial. My suggestions are as follows: remove this excess material and "re-factor" the PACE/portfolio material into one course, perhaps the capstone course. Otherwise, I learned quite a bit.

This course solidifies foundational concepts that I had trouble understanding before. but I wish it did delve deeper and added more real world examples.

Less readings and more videos are better. In the videos the tutor can be placed in the upper left corner and the rest of the screen can be used for visual learning. It is not necessary to look at the tutor all the time. Questions for Python coding should be more clear. Often, I didn't know what you exactly want. Some of the codings weren't even teached to us.

The explanations were not as easy to understand as earlier, had to look things up on youtube to understand. It lacked coherence with earlier courses like using seaborn instead of matplotlib.

Course itself was okay. The labs on Jupyter Notebooks were very buggy though.

I studied statistics years ago and I had forgotten almost all of it. Unlike my old courses though, this course was excellent in that I could see an immediate application for everything I learned.

I covered things broadly so I could do with more practice, but that is my fault because the course is designed so that you can learn things at the level you want to understand them at. There is ample practice, guidance and links to get really comfortable with both Python and, as the name suggests, the application of statistics to gain meaningful insights. I will revisit the material if I get an opportunity to perform detailed analysis, because there is still room for me to learn a lot more

It was also a very enjoyable course

The instructor's voice is gentle but he's very knowledgable and make the learning experience easy to follow. The end of course project is quite easy though.

I have never thought that statistics are that relevant to data analysis. It is complicated but the materials provided are impressive and easy to understand.

Exceptional! I've learned so much about statistics with such a clarity, and how they are being practiced in real life. Thank you, instructor!

This is but a good introduction to statistics. Not what I expected in an advanced course, but still good for beginners or as a refresh.

Many concepts aren't explained well. Overall, the course is very practical and intuitive.

Maybe a little less detail in sampling but other than that i leanred a loitttttt

Just feel textbook is better at illustrating all these concepts... but still good to learn how to use python to solve all these maths in one line.

Very boring. The audio was very low throughout. Please do something about it

An excellent lecturer, i must say his simple explanations and practical approach to all the examples makes me want to go back to study Statistics at the University.

This is the best lecture i have ever received in my entire life and i thank Google and Coursera for bringing such a talented man full of knowledge of the topic.

At the end of Week 4, i saw an Ai pop up that says 51% of people that takes this test didnt pass it as first, i smiled and said not me that paid keen attention and interest to the lecture. I pass at first instance with over 80%.

I have to conclude without mincing words that the Caption THE POWER OF STATISTICS is an appropriate coinage for the course and anyone who wants to be grounded in Data analytics must chew and drink this course.

Thank you Google et Coursera.

Course 4, 'The Power of Statistics,' in the Advanced Data Analytics specialization by Google on Coursera has been an enlightening journey. The course provided a comprehensive introduction to statistics, probability, sampling, confidence intervals, and hypothesis testing. The end-of-course project was a great opportunity to apply the newly acquired knowledge in a practical setting. This course has significantly strengthened my understanding of statistics and its pivotal role in data analysis. The clear explanations and real-world examples made the learning experience engaging and impactful. I highly recommend this course to anyone looking to solidify their statistical knowledge in the field of data analytics.

I like to thank Google team for creating this Course # 4, The Power of Statistics and video instructor(s) for presenting each concept clearly and with details. I also like to thank Coursera for hosting this course on their platform as part of Google Advanced Data Analytics Professional Certificate. By taking this course, The Power of Statistics, as part of Google Advanced Data Analytics Professional Certificate, I have understood how important it is to know statistics as part of a data analyst career. If there is raw data and if you don't apply various statistics concepts, as learned in this course, you will not be able to get insight from this data to make a logical conclusion.

All I can say is, this course is disgustingly good. It's so good that I actually feel sad finishing it and hoped it could continue longer. Every step of the way throughout this statistics course made me extremely fascinated and develop a genuine interest in this field. This has genuinely become one of my interest in life. I found myself reading up on topics related to those in this course, and even those not covered as well. That's how much interest this course has developed within me.

This is the best course of the Certificate program so far. I have learned the most from this course among the four courses I have taken. The instructor is superd and the duration of his lectures and acivities are just are also perfect that I was able to not just absorbing everything he taught but also finding interest in statistics. Great course and great instructor!

Really a great experience with this course as it covered from A to z all the aspects of statistics which is related to data analysis and the instructor was also very patiently covering all the topics related to the statistics. After completing the scores I am I am more confident on my scale of statistics and ready to apply these skills on the real world problems

This is the best statistics class I ever took, and I've taken AP Statistics and 400-level statistics courses in college. Well done, Google. The information is delivered well by the instructor. I wonder what it'd be like if Google created a college and taught these classes there. It'd probably be the most useful college in the USA.

This is a powerful tool to derive objective assessment for any business leader. Python, once you became friendly towards it, is a reliable partner in one's statistical modeling. Strongly recommend anyone with a some degree of mathematical and programming background to pursue this course.

I enjoyed this course, was really defeating since I havent seen this topic since college, however it was well structured to help understand from basic concepts as difference between descriptive and inferential statistics, to more advanced and complex as Hypothesis Testing.

Hypothesis testing is clearly explained with sufficient reference materials in case the learner needs. I also appreciate that the course provided background on the actual process of statistical computations with graphics/visuals, and not just straightly diving into code.