Again, with no formal SAS training and minimal statistics background. I found taking the first course and then this course - week after week my knowledge grew in a consistent and organized fashion.
Very good for beginners. concept explanation as well as coding were great. doesn't take too long to finish. I enrolled regression modeling course by Wesleyan and waiting to start.
par Rajat K•
par Shwathi S•
par Panji N•
par Md M H•
par Hisham Z S•
I want SAS
par Arnold A•
par Emanuela P•
This is based on their previous course (Data Management and Visualization). This course is better in terms of explaining content clearly, and I enjoyed the real-life example used when explaining about the Chi Square test. However, the python coding could be more optimized; for example, it suggests doing the Chi Square post-hoc test for each variable one by one... which can be 15 batches of dictionary recodes! Thankfully someone in the forum provided a solution for doing an automated batch testing. Maybe the course lecturers felt that a batch recode would be too complicated, but it doesn't feel like you could use their method effectively for a work environment, either. In any case, it's still a good course to explain the various data tests for quantitative and categorical data if you're new to statistics.
The instructors are pleasant, and the videos helpful. Unlike some classes where it feels like there is gulf between the toy examples covered in the lectures and what's requested in the assignments, the materials available speak directly to the homework.
The virtually non-existent discussion board, lacking much activity from either students or staff, is a real downer.
par Ashish K Y•
Thank you very much for creating this course. Basic concepts of Population, Sample, Sampling distribution, Sampling distribution variability, Hypothesis testing and ANOVA was really very helpful. the course is designed in a very nice way and the questions in between are of good standard.
par Teo S•
Very clear description of basic statistics without all the jargons and mathematical formulas behind it. Unfortunately, somehow, such a good course lacks students and the discussion forum is like ghost room with virtually zero interaction.
par Ashwani P•
Very informative. Tedious concepts like ANOVA, Chi square test etc taught in very simple and effective manner.
There're two options for analysis, SAS and Phython. I'd recommend readers to read more on PROC ANOVA for better understanding.
par Praneeth K•
This course is very good especially for beginners getting started with SAS or python for data analytics. The lessons are very clear and easy to understand. Learnt a lot of valuable information and also enjoyed it.
par Avinash S•
This was good module. It covers the basics of inferential statistical techniques along with its application using SAS/Python. I would definitely recommend to take up if you are a beginner.
It is a good course for a complete beginner in statistical inference. It helped me to understand some points I found confusing in "Statistical Inference" Coursera course.
par Abhay K•
It's one of the best course for understanding all the statistical tools , used for data sciences. Thanks to entire team for making such a wonderful course content
par Ponciano R•
It´s a really good course, I´d like it to goo deeper into the techniques but still is very useful.
par Kevin M•
Enjoyable and easy to follow along with. good videos and examples. Helped fill in some gaps.
par JOSEPH E•
This course is very interesting and every data scientist should take time and digest it.
par Claude F•
Lectures are well realized (animation, change in contexts) and peer review process.
Una buena forma de introducirte en las herramientas para el análisis de datos
par ayush t•
Videos are good and to the point.
Animation is very user friendly.