• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Classification Advanced
  • Course subject Statistics
  • Areas of interest Actuarial Studies, Finance, Statistics
  • Academic career PGRD
  • Course convener
    • Dr Hanlin Shang
  • Mode of delivery In Person
  • Offered in First Semester 2015
    See Future Offerings

This course considers statistical techniques to evaluate processes occurring through time. It introduces students to time series methods and the applications of these methods to different types of data in various contexts (such as actuarial studies, climatology, economics, finance, geography, meteorology, political science, risk management, and sociology). Time series modelling techniques will be considered with reference to their use in forecasting where suitable. While linear models will be examined in some detail, extensions to non-linear models will also be considered.

The topics will include: deterministic models; linear time series models, stationary models, homogeneous non-stationary models; the Box-Jenkins approach; intervention models; non-linear models; time-series regression; time-series smoothing; case studies. Statistical software R will be used throughout this course.

Heavy emphasis will be given to fundamental concepts and applied work. Since this is a course on applying time series techniques, different examples will be considered whenever appropriate.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

 Upon successful completion of the requirements for this course, students will be able to:

  • LO1:  Understand and apply the concept of stationarity to the analysis of time series data in various contexts (such as actuarial studies, climatology, economics, finance, geography, meteorology, political science, and sociology);
  • LO2:  Run and interpret time-series models and regression models for time series
  • LO3:  Use the Box-Jenkins approach to model and forcast time-series data empirically;
  • LO4: Use multivariate time-series models such as vector autoregression (VAR) to analyse time series data
  • LO5:  Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied time series analysis.
  • LO6:  Use existing R funtion and packages for analysing time series data, and develop their own R code for problem at the end of each chapter in teh textbook as well as additional exercises

    Other Information

    See the course outline on the College courses page. Outlines are uploaded as they become available. 

    Indicative Assessment

    • Assignments 1 - 15%
    • Assignment 2 - 25%
    • Final Examination - 60%

     

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    Workload

    Students are expected to commit 18 hours/week to completing the work.

     

    Requisite and Incompatibility

    To enrol in this course you must have completed STAT2001/STAT6039 and STAT2008/STAT6038 or enrolment in the Master of Applied Statistics

    Specialisations

    Fees

    Tuition fees are for the academic year indicated at the top of the page.  

    If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

    Student Contribution Band:
    2
    Unit value:
    6 units

    If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

    Units EFTSL
    6.00 0.12500
    Domestic fee paying students
    Year Fee
    2015 $3414
    International fee paying students
    Year Fee
    2015 $4350
    Note: Please note that fee information is for current year only.

    Offerings, Dates and Class Summary Links

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    The list of offerings for future years is indicative only.
    Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

    First Semester

    Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
    2018 16 Feb 2015 06 Mar 2015 31 Mar 2015 29 May 2015 In Person N/A

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