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Time Series Analysis in R

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4 hours
4,600 XP
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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.
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  1. 1

    Exploratory time series data analysis

    Free

    This chapter will give you insights on how to organize and visualize time series data in R. You will learn several simplifying assumptions that are widely used in time series analysis, and common characteristics of financial time series.

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    Welcome to the course!
    50 xp
    Exploring raw time series
    100 xp
    Basic time series plots
    100 xp
    What does the time index tell us?
    100 xp
    Sampling frequency
    50 xp
    Identifying the sampling frequency
    100 xp
    When is the sampling frequency exact?
    50 xp
    Missing values
    100 xp
    Basic time series objects
    50 xp
    Creating a time series object with ts()
    100 xp
    Testing whether an object is a time series
    100 xp
    Plotting a time series object
    100 xp
  2. 3

    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.

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Collaborators

Collaborator's avatar
Lore Dirick
Collaborator's avatar
Matt Isaacs

Prerequisites

Intermediate R
David S. Matteson HeadshotDavid S. Matteson

Associate Professor at Cornell University

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