I recommend this course to anyone interested in statistical analysis as an introduction to machine learning, big data, data science, etc. On a scale from 1 to 10, I give 50! A large variety of teaching approaches and tools.
Lots of practice through short tests, R-programming labs, and an in-depth project. A very lively forum with lots of help to cope with difficulties. The course is not too difficult, but the variety of the proposed material requires that students get involved quite substantially.
A very nice book available for free with plenty of practice exercises. Want more probability? The professors present concepts in lectures that have obviously been honed to a laser focus through years of pedagogical experience — there is not a single wasted second in the presentations and they go exactly at the right pace and detail for you to understand the concepts. The exercises will make you work for your knowledge and are critical for really internalizing the concepts.
This is the best online course I have taken in any subject. The competition Our 1 pick had a weighted average rating of 4. A worthy option for anyone, even those not targeting medicine.
It has a 4. No coding. Good production value. Course and instructors look really fun. Business focus. Good syllabus that uses coding. Costs money. Uses Excel. Bite-sized videos. It has a 3. I took both courses as refreshers for my undergrad statistics classes and came away with a deeper understanding. Reviews suggest prior stats experience is needed and that the course is a bit unorganized.
It has a 4-star weighted average rating over 12 reviews. One exceedingly positive review on the series and its instructors. It has a 4-star weighted average rating over 3 reviews. Life sciences focus. Biostatistics focus. Uses coding. Bad reviews. It has a 2. Short syllabus.
It has a 5-star weighted average rating over 15 reviews. The one review is really positive. It has a 5-star weighted average rating over 1 review. Need prior statistics and R knowledge. The following courses had no reviews as of November Improving your statistical inferences Eindhoven University of Technology.
Google Data Analytics Google. Probability and Statistics: To p or not to p? University of London. Guided Project. Mixed Level. Searches related to statistics.
In summary, here are 10 of our most popular statistics courses. Frequently Asked Questions about Statistics. Chevron Right What is statistics, and why is it important to learn about? This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
Other topics to explore. Arts and Humanities. Computer Science. Data Science. Information Technology. Math and Logic. Personal Development. Physical Science and Engineering. Social Sciences. Language Learning. Learn Anywhere. I am walking away really feeling like I have an introductory knowledge of statistics. Amazing teacher. I just did my final in my Stats class, and I probably did terrible. You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account.
You are commenting using your Facebook account. Notify me of new comments via email. Notify me of new posts via email. RSS - Posts. Subscribe in a reader. Email Address:. Stats With Cats Blog. Skip to content. Home About. Like this: Like Loading About statswithcats Charlie Kufs has been crunching numbers for over thirty years. He retired in and is currently working on Stats with Kittens, the prequel to Stats with Cats. This entry was posted in Uncategorized and tagged cats , matrix , measurement scales , model , Normal distribution , population , probability , samples , statistical analysis , statistical tests , statistics , stats with cats , uncertainty , variability , variables.
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