20 studying hours that helps me getting back to speed on manipulating the quantitative data in Pandas with different query conditions, powerful statistics and Sampling Distributions.

The course itself was good. I think I learnt the specific concepts well. However, I would have to go through the general sense of python to actually implement what I learnt here

Great course! It is necessary to have a minimum of knowledge in Python. If you enroll in this course, you will learn the fundamentals of statistics through Python programming.

Thanks to this course I have been able to elevate my understanding of research methodology and incorporate a more critical assessment of scientific studies into my daily work.

A really well organized course with plenty of resources to learn how to analyze and visualize data using the suite of Python packages used in statistical analysis. Loved it.

Very excellent course . Right now I know how to apply descriptive statistics in python in professional way.

Thanks coursera and University if Michigan for this opportunity.

Excelente, las clases son muy claras, presentan bastante información que ayudan a complementar los temas y los laboratorios ayudan muchisimo en el proceso de aprendizaje.

Great course if you want to get a good grasp of intro to statistics. What this course offers is a great content on how to use proper statistical modelling for research.

Very good course instructors ! Excellent balance of basics of statistics and python programming oriented towards data analysis. Thoroughly enjoyed the course material.

Great course to learn about the basic tools which will be helpful in data visualization and this course also gives an insight explanation of where the data comes from.

The course is very good & it gives a confidence to people like me who are new to Python .

It would be great If you can explain the hypothesis section in more detail .

Really helpful to build a foundation for the basic Python and improve the understanding on basic but key concepts on statistics and visualizing techniques. Awesome!

It's a very nice course, which narrows complicated statistics concepts to understandable size, additionally, each concept is explained through hands-on exercises!

its more benificial for me becasuse visulization of the data is very important understand in analysis part that i have gained very easy from you thankyou so much

The course is comprehensive and good for beginners. Highly recommend if you are starting out as a data scientist or even if you are a beginner python programmer.

excellent course. if want to know what is data data and want to visualize data then you should do this course. Excellent course material, videos, quiz and more.

That is a wonderful course . I learn a lot of things . I love it . The introduction of course by Brenda Gunderson is amazing . and other instructor are also .

Very informative course! helps you increase your depth of knowledge in Statistics. Would highly recommend to any aspiring Data Analysts and Data Scientists.

It is a very explanatory course with instructors trained in the subject. The class materials are varied, which allows new technical skills to be developed.

It's a very good course to learn statistics for data analysis and data science. The instructors were great and the information they gave was just precious.

Great course to review basic statistical concepts. The added component of python was a practical way to learn python and apply it to real situations.

i like it , some of the topic in this course was hrad to deal with such as nonprobability sampling

but for all course was sucessful , thanks alot

Well, those sampling courses couldn't be more beneficial. It answered many questions i my mind. Thanks Umich and Coursera for the solid course!

The course provides basic knowledge and concepts of statistics in Python, which is very useful for someone who aims at the data science career.

Great course! Tons of useful materials, allocation of topics and workload corresponds to the course level and time indicated to complete them.