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Practical Time Series Analysis, The State University of New York

334 个评分
87 个审阅


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!...


创建者 MS

Feb 28, 2018

I have not completed the course yet, working on week 5. If you have some Math background, this course gives a good practical introduction to Time Series Analysis. I recommend it.

创建者 RS

Mar 18, 2018

Really great lectures and clearly explaining the concepts and complicated models. In my opinion, a bit of practical applications of these models on Panel Data should be included.


87 个审阅

创建者 xun yu

Dec 16, 2018

Great introductory course on time series. Focus on ARIMA model most of the time while the last lecture capture a little bit of exponential smoothing. Would be great if there if summary lecture regarding to when to use which modeling technique. would be even better if there is a optional lecture to cover some of the more advanced time series models.

创建者 Asif Lakhany

Nov 30, 2018

A very good course taught by equally good instructors. Highly recommended.

创建者 戚兆禹

Nov 30, 2018

good learn something new

创建者 Al Amin Mridha

Nov 26, 2018

Good! but Theoretical terms were little bit boring & confusing.

创建者 Vidhyalakshmi K

Nov 24, 2018

The course is very insightful substantively covering both theory and practical in a balanced manner. I liked it very much.

创建者 Ahmad Lutfi

Nov 24, 2018

great course even for newbies who're learning R.

创建者 Hilmi Erdem

Nov 21, 2018

Good practical overview with lots of exercises

创建者 Jose Lucas Araujo

Nov 18, 2018

The course gives really useful skills regarding time series analysis, but it seems a little bit forgotten by the authors since some links in the during the course are not working anymore ( for instance the link describing whether a seasonality is addictive or multiplicative "". Also,there are time a future content is presented before the class in some questions, as is the case the moving average week where there is a question regarding auto regressive process, a content present in future classes. Besides those points, the classes and material are really helpful, and i can say that this skills learned will sure be used in my professional life


Nov 16, 2018

Excellent course. Well Structured with sufficient lectures, practical examples and quizzes. Strongly recommended.

创建者 Robert Schmitt

Nov 11, 2018

The instructors provided detailed background for the theoretically inclined while gradually developing practical implementations in R using many real time series. Having finished the course I have a firm grasp of the process of analyzing time series and forecasting from them, as well as greater general facility in R. Overall an excellent and useful course.