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The State University of New York

Practical Time Series Analysis

Tural Sadigov
William Thistleton

Instructors: Tural Sadigov

91,541 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.6

(1,688 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 25 hours
Learn at your own pace
90%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.6

(1,688 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 25 hours
Learn at your own pace
90%
Most learners liked this course

Details to know

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Assessments

19 assignments

Taught in English

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There are 6 modules in this course

During this first week, we show how to download and install R on Windows and the Mac. We review those basics of inferential and descriptive statistics that you'll need during the course.

What's included

12 videos4 readings2 assignments3 ungraded labs

In this week, we begin to explore and visualize time series available as acquired data sets. We also take our first steps on developing the mathematical models needed to analyze time series data.

What's included

10 videos1 reading3 assignments1 ungraded lab

In Week 3, we introduce few important notions in time series analysis: Stationarity, Backward shift operator, Invertibility, and Duality. We begin to explore Autoregressive processes and Yule-Walker equations.

What's included

13 videos7 readings4 assignments

In this week, partial autocorrelation is introduced. We work more on Yule-Walker equations, and apply what we have learned so far to few real-world datasets.

What's included

8 videos3 readings3 assignments4 ungraded labs

In Week 5, we start working with Akaike Information criterion as a tool to judge our models, introduce mixed models such as ARMA, ARIMA and model few real-world datasets.

What's included

7 videos6 readings4 assignments2 ungraded labs

In the last week of our course, another model is introduced: SARIMA. We fit SARIMA models to various datasets and start forecasting.

What's included

10 videos6 readings3 assignments2 ungraded labs

Instructors

Instructor ratings
4.6 (382 ratings)
Tural Sadigov
The State University of New York
1 Course91,541 learners
William Thistleton
The State University of New York
1 Course91,541 learners

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Recommended if you're interested in Probability and Statistics

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4.6

1,688 reviews

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