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學生對 纽约州立大学纽约州立大学 提供的 Practical Time Series Analysis 的評價和反饋

4.6
1,410 個評分
404 條評論

課程概述

Welcome to Practical Time Series Analysis! Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics. In practical Time Series Analysis we look at data sets that represent sequential information, such as stock prices, annual rainfall, sunspot activity, the price of agricultural products, and more. We look at several mathematical models that might be used to describe the processes which generate these types of data. We also look at graphical representations that provide insights into our data. Finally, we also learn how to make forecasts that say intelligent things about what we might expect in the future. Please take a few minutes to explore the course site. You will find video lectures with supporting written materials as well as quizzes to help emphasize important points. The language for the course is R, a free implementation of the S language. It is a professional environment and fairly easy to learn. You can discuss material from the course with your fellow learners. Please take a moment to introduce yourself! Time Series Analysis can take effort to learn- we have tried to present those ideas that are "mission critical" in a way where you understand enough of the math to fell satisfied while also being immediately productive. We hope you enjoy the class!...

熱門審閱

SS
2021年4月6日

It is a very good course which builds on the basics of time series and also covers more advanced topics like SARIMA. The course contains ample examples which helped me better understand the material.

SA
2020年1月23日

Excelente, uno de los mejores cursos que he tomado. Lo más importante es que se practica muy seguido y hay examenes durante los vídeos. Si hay un nivel más avanzado de este tema, seguro que lo tomo.

篩選依據:

251 - Practical Time Series Analysis 的 275 個評論(共 409 個)

創建者 rashid K

2019年7月9日

very useful course

創建者 Ruiliang L

2018年10月6日

Easy to understand

創建者 Steven A L

2020年8月7日

Very challenging

創建者 Arunava B

2020年5月30日

Very good course

創建者 Swarn

2020年2月24日

Excellent class!

創建者 Yuan C

2018年4月5日

Very nice course

創建者 Edilson S

2019年6月6日

Amazing Course!

創建者 Marek D

2020年1月26日

Great content!

創建者 CHENG Y T

2018年6月28日

Very practical

創建者 Deleted A

2018年6月5日

Amazing course

創建者 Ashutosh M

2021年1月5日

best course..

創建者 刘思航

2018年10月24日

very helpful!

創建者 Yu Q

2018年7月18日

Very helpful!

創建者 Gabriel A C N

2020年6月21日

Excelente!!!

創建者 Juan L R A

2020年5月27日

Nice course

創建者 Moises B J

2021年5月10日

Excelente

創建者 Roberto G A

2019年5月23日

Excellent

創建者 Alireza P

2020年7月22日

Perfect

創建者 ِِِAli A A

2020年7月16日

perfect

創建者 Douglas B P

2018年9月2日

Great!!

創建者 Cathy D

2018年5月22日

useful!

創建者 Alla E G

2020年1月18日

Thanks

創建者 GAUTAM T

2021年7月31日

good

創建者 Ganesh

2020年6月4日

Good

創建者 D. R

2019年11月9日

I'm in week 5, and I think that this course is interesting and you learn from it. However it is done in a somewhat sloppy manner, to my taste.

My biggest problem is the notations and equations are a bit of mess. Beta's in one equation are replaced with phi's in another (sometimes in the same "lecture" slides) or theta's - there's just no real coherent notation. The formulas are brushed through, and they contain mistakes (a product of this sloppy notations), e.g. pi(beta) is missing the beta (which is what it depends on! week5, ARMA properties and a little theory). The R code is also sloppy, for example you see them setting variables in the first cell, and then never using them in the next cell. Or calculating variance using a cumbersome call to an acf function telling it to bring back the autocovariance, and taking the first term. TL;DR - It's just sloppy.

There are no exercises, but the quizzes contain some code you can run. Not enough for really drilling the material into you, though.

In general, I think this course could really improve, and I would like to see it do so. As a general introduction to the topic it might be decent enough.