This is the third course in the Google Advanced Data Analytics Certificate. In this course, you’ll discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. You'll also learn how to use Python for statistical analysis and practice communicating your findings like a data professional. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the eight courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Describe the use of statistics in data science -Use descriptive statistics to summarize and explore data -Calculate probability using basic rules -Model data with probability distributions -Describe the applications of different sampling methods -Calculate sampling distributions -Construct and interpret confidence intervals -Conduct hypothesis tests
I absolutely loved the balanced approach between fundamental concepts and insightful hints on more advance topics in statistics. The instructor explained hard concepts using easily-digestible content!
it's very good course ever, and extreme defficult for me as well. thank you Google and Coursera team for producing a good course like this
Great instructor, I really liked the way he kept repeating key concepts, it helped me get them fixed on my mind, thanks for this course!
If you're a UX professional and want to feel more confident presenting survey results or comparing results (e.g. comparing a new score against a benchmark score), I highly recommend this course!
It was quite a technical course and got harder along the way. However the course content made catching up with the technical courses highlighted in this course easier.
This course solidifies foundational concepts that I had trouble understanding before. but I wish it did delve deeper and added more real world examples.
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.
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.
i loved learning about stats as i am always interested in it and know more about stats. thank you Evan sir
Pretty good to start your journey. Doesn't go TOO deep but still more than good enough. Loved the instructor and the python practice lab part. Very helpful.
I’m so grateful for the excellence, well crafted and clearly delivered career-oriented course you have offered.
Informative , practical and knowledge well shared and explained by the instructor. Really grateful that i have the skills to apply statistics in data analysis.
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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.
Exceptional! I've learned so much about statistics with such a clarity, and how they are being practiced in real life. Thank you, instructor!
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.
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.
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.
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
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.
I found the Google Advanced Data Analytics course to be very good and highly beneficial. It has helped me build strong skills and gain confidence in data analytics. The course content is practical, industry-focused, and easy to follow, which makes it very helpful for me to grow and establish myself in this field. I truly recommend it to anyone looking to step up in the data analytics industry.