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STAT 5170

Applied Time Series

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Course Description

Pre-Requisite(s): STAT 3120

Studies the basic time series models in both the time domain (ARMA models) and the frequency domain (spectral models), emphasizing application to real data sets. Conceptual discussion in lectures is supplemented with hands-on practice in applied data-analysis tasks using SAS or R statistical software.


  • Dan Spitzner
     Rating

    1.00

     Difficulty

    5.00

     GPA

    3.24

     Sections

    —

    Last Taught

    Fall 2022

  • Taylor Brown
     Rating

    2.58

     Difficulty

    4.50

     GPA

    3.40

     Sections

    —

    Last Taught

    Fall 2020

  • Jeffrey Woo
     Rating

    3.50

     Difficulty

    4.17

     GPA

    —

     Sections

    —

    Last Taught

    Spring 2023

  • Daniel Keenan
     Rating

    2.33

     Difficulty

    2.33

     GPA

    3.36

     Sections

    —

    Last Taught

    Spring 2019

  • Jianhui Zhou
     Rating

    —

     Difficulty

    —

     GPA

    3.76

     Sections

    —

    Last Taught

    Fall 2019

  • Caitlin Steiner
     Rating

    —

     Difficulty

    —

     GPA

    3.14

     Sections

    —

    Last Taught

    Spring 2017

  • Faculty Staff
     Rating

    —

     Difficulty

    —

     GPA

    —

     Sections

    —

    Last Taught

    Fall 2015

  • Yong Woo
     Rating

    —

     Difficulty

    —

     GPA

    3.47

     Sections

    —

    Last Taught

    Spring 2016

  • To Announced
     Rating

    —

     Difficulty

    —

     GPA

    —

     Sections

    —

    Last Taught

    Fall 2025