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.

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 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.

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!

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

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.

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.

I did have a generalized understanding to statistics, but this class showed me I had room to grow. Corrected my understanding of statistics all the way around and it also helped with effective examples as well to help reinforce the concepts. Highly recommended.

This course explained statistical methods thoroughly and in a way that was easy to understand. I wasn't looking forward to this part of the course but came away with a solid appreciation for how statistics can be applied in and is essential to data analysis.

Excellent course structure and content. Very useful for whoever wants to understand the role of Statistics in the Data professions at a starting point. I personally enjoined it and I really feel that I learned a lot. This program is outstanding !!!

This instructor is so good. He summarized what I learn at school so well and even goes further in breaking down flummoxing topics such as Confidence Interval. Highly recommend this course for any data analyst professionals.

a good course to learn more about general statistics and its applicability for data science in python, i think it is just needed more programming exercises, but in general good way to explain this topics from the teacher.

This was so good I have decided to learn more in this field. As a complete nubbie...I love how they focused on key concepts, this made me feel I at least had the potential to do more in this exciting field.

Course is great Instuctor has used very simple example to understatnd complex things. this course has really augment my statisctics knowledge. Thank You Course Instructor and his Team . Thanks Coursera ..