ST3010: Applied Forecasting
Michaelmas Term 2017
Lecturer: Rozenn Dahyot
TA: Matej Ulicny
Timetable
 910am Monday Lecture in LB01 Lloyd Building
 45pm Monday Lecture in LB01 Lloyd Building
 1011am Friday Lecture LB04 Lloyd Building
Foreword
5 ECTS module corresponds to about 100125 hours of study time. This includes the 30+ hours of lectures organised on campus that students have to attend. Other sources of information are available to help you (e.g. online ressources such as webpages, videos, MOOCs, and books in TCD libraries). Be creative and independent to build up your skills!
Contacting the lecturer
Emails from students in my taught modules are automatically deleted without being read for logistic and time management reasons. Ask questions during classes so be there!
R Software
Playing with data is an important part of Statistics modules. Help is given on this webpage for using R in the context of time series. It is advised to do this labs on your own study time to get to be familiar with using R for forecasting.
Lecturenotes
All lecturenotes may not be available electronically. It is advised to come to classes and take notes. Some incomplete Lecturenotes are available. Some additional slides and exercises are available Blackboard.
References
There are a lot of books on time series, forecasting in the Library that are relevant to the course. Below the first book is given as an example reference. It is available in the library and most of the time series used in the labs are explained in that book.
 Forecasting  Methods and Applications S. Makridakis, S. C. Wheelwright and R. J. Hyndman, Wiley
 Forecasting: principles and practice online book by R. Hyndman and G. Athanasopoulos
Weekly timeline
 W1: Introduction, SES and DES algorithms.
 W2: Seasonal HoltWinters algorithms (see chapters 5 to 8 Lecturenotes and Blackboard)
 W3: ACF/PACF  Linear model, AR(1)
 W4: Least Square algorithm, AR(p) models
 W5: ARIMA(p,d,q)

W6: (Monday bank Holiday)  Friday: mock inclass test.
 Some answers of the mock test computed in R
 W7: Reading week

W8: ARIMA(p,d,q)
 9am Monday: Inclass test 25% : bring non programmable calculator.
 4pm Monday: Backshift operator
 Friday: Ex.1 Trinity Exam 2017
 W9: Seasonal ARIMA models
 W10:
 W11:

W12:
 9am Monday: Inclass test 25% : bring non programmable calculator.
 Monday 4pm + Friday: Assignment
Exam/Assessment
First session 100% Assessment (no exam in Trinity term 2018): 2 inclass tests (25% each) in weeks 8 and 12 (50 minutes, on Mondays 9am lectures).
 Individual time series analysis: report + R code + time series to submit on blackboard (Monday 8th January 2018)
 Repeat Exam 100% (Michaelmas term 2018)
After exam results
Read What if I want my examination rechecked? and What if I wish to appeal my results?. Request to see script should be made to the SCSS Teaching Unit ( teachingunit @ scss.tcd.ie ) with the following information:
 Exam number of the student
 Code of the module (e.g. ST3010)
 Exam session (e.g. Trinity term, Michaelmas term (supplementals))
Note that marks can not be haggled or changed for other reasons than specified in TCD calendar: a third party (staff member other than lecturer) will also be there monitoring this meeting. Such meeting is not an opportunity for a private tutoring session nor for getting tips for supplementals.