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Вернуться к Инструменты анализа данных

Отзывы учащихся о курсе Инструменты анализа данных от партнера Уэслианский университет

Оценки: 407

О курсе

In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work....

Лучшие рецензии


19 дек. 2015 г.

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.


2 дек. 2015 г.

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.

Фильтр по:

51–75 из 91 отзывов о курсе Инструменты анализа данных

автор: Kanda K K

22 нояб. 2020 г.

the course was good

автор: Ichsan H

8 февр. 2016 г.

Easy to understand!

автор: Rajat K

8 окт. 2016 г.

Intersting Mentor.

автор: Swatato

9 авг. 2016 г.

Really good!

автор: Panji N

3 мая 2018 г.

Good course

автор: Md M H

17 февр. 2017 г.


автор: Guan

28 дек. 2015 г.


автор: Hisham Z S

6 июня 2017 г.

I want SAS

автор: Arnold A

9 июня 2016 г.

Very nice!

автор: Emanuela P

6 янв. 2016 г.


автор: acampagnolo

27 нояб. 2015 г.


автор: ngoduyvu

16 февр. 2016 г.


автор: Emily

21 янв. 2018 г.

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.

автор: Jessica

28 янв. 2016 г.

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.

автор: Ashish K Y

23 мар. 2017 г.

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.

автор: Siyang

1 авг. 2016 г.

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.

автор: Ashwani p

30 июня 2016 г.

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.

автор: Praneeth K

2 авг. 2016 г.

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.

автор: Avinash S

9 февр. 2017 г.

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.

автор: Maria D P H M

16 авг. 2021 г.

Excelente. Buenas herramientas y buena explicación. Los videos en python falto los subtítulos en spanish, quede muy interesada en aprender desde python pero el idioma no lo domino.

автор: Asier

10 мар. 2016 г.

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.

автор: Abhay K

23 февр. 2016 г.

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

автор: Ponciano R

15 янв. 2019 г.

It´s a really good course, I´d like it to goo deeper into the techniques but still is very useful.

автор: Kevin M

12 сент. 2016 г.

Enjoyable and easy to follow along with. good videos and examples. Helped fill in some gaps.

автор: JOSEPH E

25 янв. 2016 г.

This course is very interesting and every data scientist should take time and digest it.