Practical Time Series Analysis
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!
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Syllabus
Syllabus - What you will learn from this course
Week 1
WEEK 1: Basic Statistics
Week 2
Week 2: Visualizing Time Series, and Beginning to Model Time Series
Week 3
Week 3: Stationarity, MA(q) and AR(p) processes
Week 4
Week 4: AR(p) processes, Yule-Walker equations, PACF
Week 5
Week 5: Akaike Information Criterion (AIC), Mixed Models, Integrated Models
Week 6
Week 6: Seasonality, SARIMA, Forecasting
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
A good course to start up with time series forecasting. The code meets its objective of teaching practical time series analysis. Though, a little more theory on the same would be appreciated
The structure of first 2-3 weeks can be improved. The initial flow seems to be jumping, I thought I am not getting it, but I see the same feedback in discussion forum, so I am clearly not alone.
I think I need support on the very last week, namely, week 6, on the very first quiz. I don't understand the answers on how they were derived but I was able to get the answers by repeating the quiz.
Great introduction to time series with plenty of depth. Really enjoyed the instructors and loved the frequent assessments rather than a big project. Highly recommended
