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Introduction to Time Series Analysis

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  • 16 Videos
  • 58 Exercises
  • 4 hours 
  • 5,153 Participants
  • 4600 XP

Instructor(s):

David S. Matteson
David S. Matteson

David S. Matteson is Professor of Statistical Science at Cornell University and co-author of Statistics and Data Analysis for Financial Engineering with R examples.

Collaborator(s):

Lore Dirick Lore Dirick

Matt Isaacs Matt Isaacs

Course Description

Many phenomena in our day-to-day lives, such as the movement of stock prices, are measured in intervals over a period of time. Time series analysis methods are extremely useful for analyzing these special data types. In this course, you will be introduced to some core time series analysis concepts and techniques.

Correlation analysis and the autocorrelation function 

In this chapter, you will review the correlation coefficient, use it to compare two time series, and also apply it to compare a time series with its past, as an autocorrelation. You will discover the autocorrelation function (ACF) and practice estimating and visualizing autocorrelations for time series data.