161.342 Forecasting and Time Series (15 credits)

A practical course on analysing data that arise sequentially in time (e.g. sales figures, precipitation, crime rates, census figures, share prices, etc.). Detecting trends and underlying seasonal patterns; Box-Jenkins methodology, autoregressive and moving average processes; exponential smoothing, classical decomposition and regression methods; introduction to multivariate time series; simulation.

Note(s): Access to a Windows PC with an approved statistics package is required for analysis of data.

Requirements Requirements help

Offerings Offerings help

Year Semester Mode Location
2017 Semester Two full semester Internal Manawatu Campus
2017 Semester Two full semester Distance
2018 Semester Two full semester Internal Manawatu Campus
2018 Semester Two full semester Distance

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